Enhanced Multispectral Polarimetric Imaging Techniques

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ENHANCED MULTISPECTRAL POLARIMETRIC IMAGING TECHNIQUES

UTILIZING AN OPTICAL TUMOR PHANTOM

A Thesis

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Srinivasan Sukumar

August, 2005

ENHANCED MULTISPECTRAL POLARIMETRIC IMAGING TECHNIQUES

UTILIZING AN OPTICAL TUMOR PHANTOM

Srinivasan Sukumar

Thesis

Approved: Accepted:

______Advisor Dean of the College Dr. George C. Giakos Dr. George K. Haritos

______Faculty Reader Dean of the Graduate School Dr. Narender P. Reddy Dr. George R. Newkome

______Department Chair Date Dr. Daniel B. Sheffer

ABSTRACT

The purpose of this research was to investigate the potential of a laser-based optical polarimetric imaging system, operating under light backscattering geometry, for tumor detection utilizing an optical tumor phantom. Image plays a key role in tumor detection studies. The polarization state of the scattered light from a tumor-like structure and the discrimination of randomly polarized light from weakly polarized light can provide meaningful information regarding the nature of the tumor itself. This information can be both physiological and structural. In this research study, experiments were performed at two optical wavelengths, one visible and one near-infrared wavelength. The weakly scattered light from the tumor tissue like phantom had the necessary information relevant to the structure of the tumor. A Rotating Retarder Polarimeter was used to analyze this weakly scattered light from the phantom. The images obtained from the Rotating

Retarder Polarimeter were then processed by means of a data reduction algorithm, based on Polarimetric Measurement matrix method to calculate the Degree of Linear

Polarization (DOLP) image. Then, the DOLP images obtained from the two different wavelength lasers were subtracted to enhance the information present in the image.

The Signal-to-Background ratio, a measure of contrast, was calculated to determine the quality of the image. Results from the experiments and the contrast analysis procedures showed that, the subtracted DOLP images provides better contrast in terms of

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higher numerical value compared to the single DOLP image. Overall, this optical imaging system combined with data reduction algorithm and image processing technique served as an effective imaging methodology in optical tumor phantom study.

DEDICATION

I dedicate this thesis to my Grandmother, Laxmi Ammal.

ACKNOWLEDGEMENTS

I still remember the first day when I went and met Dr. Giakos. He has truly inspired me in more than one ways. He has been supportive to me from day one and I am greatly indebted to him for that. I owe all my academic success during this master’s degree to

Dr. Giakos who has been more than an advisor to me. Thank you so much for all that you have done to me during this past 12 months. My committee members, Dr. Daniel Sheffer and Dr. Narender Reddy have been very much understanding and I am thankful to them for their support and valuable advices. Ms. Bonnie Hinds, what should I say, she had been a wonderful person and was always ready to help me, whenever I needed them the most. I would like to thank Mr. Rick Nemer from the Biomedical Engineering department. I would also like to extend my sincere thanks to all the faculty members of the Biomedical Engineering department.

Dad, I owe you everything that I have achieved in my life till now. You have stood by me in almost all my endeavors and I feel I am nowhere without your support. Mom, I just love you for your innocence and unconditional love for me. Your prayers have worked wonders for me. Ramesh, you have been the best brother I could ever ask for.

Also, my sister in law, Vahini has been supporting me right from the day she walked into my life. Thank you for being there for me. At this point I would like to extend my sincere gratitude to my uncle Pitchandi and aunt Parimala. They are the sole reason for me being here in United States. vi

My colleagues, Abhilasha and Shadi Sumrain were always there to help me during my nervous initial days in the lab. Abhilasha has been a great friend and philosopher to me. I am very thankful to her for her advices and support. Shadi, you have amazed me by your activities and the starting point of my thesis was mainly due to your DOLP algorithm. I am extremely thankful to you for that, as well as, your valuable advices.

My friends Senthil ram, Rajdeep and Praveen have been very supportive to me and went out of the way to help me out in most of the occasions. I am extremely thankful to them for being there for me.

My FFSG friends are my greatest possession in my life. Their influence on me is way beyond explanation and I am more than thankful to them for their unconditional love and support. At this point I would like to thank Sowjanya, who had made me mature in more than one ways.

I am thankful to all my friends over here and back in India for their love, support, criticism and encouragement.

My fiancé and my better half, Shyamala has been my lover, friend, philosopher.

Right from the day she entered my life, she has took me by surprise in most of the occasions. She has been thoroughly supportive and understanding throughout, especially during the lean patches of my life. Shyamala, I love you so much.

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TABLE OF CONTENTS

Page

LIST OF TABLES…………………………………………………………………. ….. xi

LIST OF FIGURES…………………………………………………………………...... xii

CHAPTER

I. INTRODUCTION..………………………………………………………………... 1

1.1 General Introduction…………………………………………………………... 1

1.2 Problem Definition…………………………………………………………….. 3

1.3 Objectives of the Study………………………………………………………... 4

1.4 Research Hypothesis……………………………………………………...... 5

1.5 Limitations of the Study……………………………………………………….. 5

II. LITERATURE REVIEW………………………………………………………….. 6

2.1 Optical imaging techniques using polarization……………………………….. 6

2.2 Optical imaging techniques based on Mueller matrix formalism…………….. 7

2.3 Image subtraction techniques…………………………………………………. 8

2.4 Optical properties of biological tissues……………………………………….. 9

III. THEORY…………………………………………………………………………. 10

3.1 Laser interaction with tissue…………………………………………………. 10

3.2 Polarized light………………………………………………………………... 11

3.3 Multispectral imaging………………………………………………………... 13

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3.4 Polarimetric imaging…………………………………………………………. 13

3.5 Stokes parameter………………………………………………...... 14

3.6 Mueller matrix……………………………………………………………….. 14

3.7 Multispectral Polarimetric imaging………………………………………….. 15

IV. EXPERIMENTAL SETUP AND PROCEDURES………………………………. 17

4.1 Preclinical Phantom Design………………………………………………….. 17

4.2 Experimental Setup…………………………………………………………... 19

4.3 Experimental Procedure……………………………………………………… 20

4.4 Alignment and Calibration Procedures………………………………………. 21

4.5 Data Reduction Algorithm…………………………………………………… 22

4.6 Analysis Technique…………………………………………………………... 25

V. MATERIALS……………………………………………………………………... 27

5.1 Optical Tabletop………………………………………………………...……. 27

5.2 Lasers………………………………………………………………………… 28

5.2.1 Semiconductor Laser…..…………………………………………… 28

5.2.2 Infrared Laser……………………………………………………….. 28

5.3 Linear Polarizer………………………………………………………………. 29

5.4 Retarder………………………………………………………………………. 29

5.4.1 Berek compensator………………………………………………….. 30

5.5 Beam Expander………………………………………………………………. 31

5.6 CCD Camera…………………………………………………………………. 32

5.7 Polystyrene sphere………………………………………………………...... 32

5.8 Intralipid…………………………………………………………………….... 32

VI. RESULTS AND DISCUSSIONS………………………………………………… 35

6.1 Single DOLP images………………………..………………………………... 35

6.2 Back-Scattered Mode Single DOLP images and their intensity plots……….. 37

6.3 Inferences from single DOLP images………………………………………... 43

6.4 Subtracted DOLP images………………………..………………………...... 44

6.5 Subtracted DOLP images and their intensity plots…………………………... 46

6.6 Inferences from subtracted DOLP images………………………………...... 52

6.7 Intensity measurements of the signal and the background and inferences...... 53

6.8 Signal-to-Background contrast ratio measurements and inferences…………. 54

VII. CONCLUSION AND FUTURE WORK………………………………………… 56

REFERENCES…………………………………………………………………………. 57

LIST OF TABLES

Table Page

5.1 Specifications of the 1135P JDS Uniphase Helium-Neon laser…………………… 28

5.2 Specifications of the IS785-25 model, IR Laser system…………………………… 29

5.3 Specifications for the beam expander…………………………………………...... 31

5.4 Specifications for the CCD Camera………………………………………………... 32

6.1 Average intensity value measurements of the signal and the background for solution 1……………………………………………………………………….. 53

6.2 Average intensity value measurements of the signal and the background for solution 2…………………………………………………………………...... 53

6.3 Signal-to-Background contrast ratio measurements for solution 1………………… 55

6.4 Signal-to-Background contrast ratio measurements for solution 2………………… 55

LIST OF FIGURES

Figure Page

3.1 Paths traced by light in a tissue…………………………………………………….. 10

3.2 Linearly polarized light………………………………………………………...... 12

3.3 Circularly polarized light………………………………………………………...... 12

4.1 Phantom for tissue infected with tumor…………………………………………..... 18

4.2 The experimental Setup……………………………………………………...... 19

5.1 The Melles Griot StableTop™ tabletop with triple-plate, double-honey comb-core construction includes TurboClean™ sealed mounting holes….….…… 27

5.2 Berek compensator…………………………………………………………………. 30

5.3 Side view of Berek compensator showing various alignment screws……………... 30

5.4 Photograph of the experimental setup with semiconductor laser………………….. 33

5.5 Photograph of the experimental setup with near-infrared laser….………………… 33

5.6 Photograph of the preclinical phantom used in the experiment…………………..... 34

6.1 DOLP for solution 1 (633nm) ……………………………………………………... 37

6.2 Intensity plot for the region within the polystyrene sphere (solution 1).………...... 37

6.3 Intensity plot for the region outside the polystyrene sphere (solution 1)………...... 38

6.4 DOLP for solution 1 (785nm)……………………………………………………… 38

6.5 Intensity plot for the region within the polystyrene sphere (solution 1)………...... 39

6.6 Intensity plot for the region outside the polystyrene sphere (solution 1)………...... 39

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6.7 DOLP for solution 2 (633nm)…………………………….………………………... 40

6.8 Intensity plot for the region within the polystyrene sphere (solution 2)………...... 40

6.9 Intensity plot for the region outside the polystyrene sphere (solution 2)………...... 41

6.10 DOLP for solution 2 (785nm)…………………………………………………….. 41

6.11 Intensity plot for the region within the polystyrene sphere (solution 2)….……..... 42

6.12 Intensity plot for the region outside the polystyrene sphere (solution 2)……….... 42

6.13 Subtracted DOLP for solution 1 (633nm-785nm)………………………………... 46

6.14 Intensity plot for the region within the polystyrene sphere (solution 1)………...... 46

6.15 Intensity plot for the region outside the polystyrene sphere (solution 1)……….... 47

6.16 Subtracted DOLP for solution 1 (785nm-633nm)………………………………... 47

6.17 Intensity plot for the region within the polystyrene sphere (solution 1).………..... 48

6.18 Intensity plot for the region outside the polystyrene sphere (solution 1)……….... 48

6.19 Subtracted DOLP for solution 2 (633nm-785nm)………………………………... 49

6.20 Intensity plot for the region within the polystyrene sphere (solution 2)…….…..... 49

6.21 Intensity plot for the region outside the polystyrene sphere (solution 2)……….... 50

6.22 Subtracted DOLP for solution 2 (785nm-633nm) ……………………………….. 50

6.23 Intensity plot for the region within the polystyrene sphere (solution 2)………...... 51

6.24 Intensity plot for the region outside the polystyrene sphere (solution 2)……….... 51

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CHAPTER I

INTRODUCTION

1.1 General Introduction

Early detection of a tumor is an extremely important step in the diagnosis and treatment of cancer. Any abnormality or hidden structures in the body are basically identified by four major imaging modalities. These imaging techniques are based on:

a) X-rays, such a classical film technology, digital radiography, Computed

Tomography (CT)

b) Ultrasound

c) Nuclear medicine, such as Single-Photon Emission Computed Tomography

(SPECT), Positron Emission Tomography (PET)

d) Magnetic resonance

X-Ray imaging techniques are good in distinguishing soft from hard tissue. However, they become extremely unreliable in distinguishing a tumor among soft tissues due to the close similarity of the linear attenuation coefficients in soft tissue media. Ultrasound imaging techniques are non-invasive, as well as, inexpensive, quick and convenient that can provide good resolution but has a mediocre spatial resolution [1]. Nuclear medicine techniques have been mostly applied for the metastatic cancers (i.e., bone cancer) [2].

PET opens new horizons in tumor detection, by contributing to the accurate staging of cancer (i.e., lymphoma cancer) with a certain success [2]. As a result, tumor treatment 1

and response to cancer treatment can be tailored on an individual basis, increasing the chances for more successful treatment of cancer. Magnetic resonance imaging provides images with better cross sectional views. These images have good spatial and contrast resolution. Hence, they can be effectively used for detecting and locating cancer in brain and spinal cord, head, neck and musculoskeletal system. However, this technique is expensive and has unexplored clinical potential to different types of cancer [3].

On the other hand, optical imaging is a new area of research, which hopefully can be applied alone, or in conjunction with other imaging modalities, leading to early diagnosis and accurate assessment of disease. In the recent years, new imaging techniques with the help of light are gaining widespread application in the medical field.

Light based techniques are becoming an increasingly popular method of probing heavily scattering media such as body tissue [4]. Optical imaging techniques are noninvasive, relatively portable, and economical and do not require injection of contrast agents compared with PET and MRI [5] .The development of tumor in tissues alter the refractive index, tissue density and chemical composition of the tissue. Change in refractive index of the tissue causes a change in the optical scattering. Hence, optical imaging techniques are ideally suitable for early detection of tissue abnormalities than the existing imaging modalities [6]. Also, optical imaging techniques offer greater potential in terms of providing an eminently practical field for carrying out tumor detection experiments. The use of lasers in these optical imaging techniques only adds to the already existing list of advantages. Medical imaging with laser radiation is gaining importance for early detection of cancer. This imaging technique is based on refractive index variation, a sensitive parameter, in contrast to those used in other diagnostic techniques [6].

The success of any medical imaging technique is based on its ability to effectively acquire images of various structures of the body that provide vital information with regard to clinical diagnosis and treatment of the affected portion under scrutiny. Any image obtained using medical imaging techniques has basically two parts, the object of interest and the background or noise. Differentiating the region of interest from the unwanted background poses a major problem in the analysis of images. The sharpness of the object of interest against the background depends mainly on the amount of scattering undergone by the light interacting with the target. The light that propagates the shortest distance between the object and the image plane forms a sharp image [7]. Polarization based discrimination between the weakly scattered light and the strongly scattered light is based on the fact that weakly scattered light retains it polarization state while the strongly scattered light does not [8].

Analyzing the quality of an image forms the final step in evaluating the success of an imaging system. In visual perception, contrast is the difference in visual properties that makes an object distinguishable from other objects and the background. Hence, target

(object of interest) detection becomes easier with higher value of contrast.

1.2 Problem Definition

Giakos has introduced the Multispectral, Multifusion Polarimetric Imaging techniques to various areas from Biophotonics to semiconductor wafer inspection [9]-

[11]. The above theory fuses spectral polarimetric differences (DOLP differences and

Mueller matrix differences acquired at different wavelengths) based on the complete polarimetric characterization of target. Various other polarimetric imaging techniques

like contrast enhanced optical imaging of submersible targets to image targets in highly turbid medium [12] and Mueller matrix based optical imaging with application to tissue diagnostics were done using rotating retarder setups [13].

Imaging of targets in a medium with both scattering and absorption substances remains to be done using polarization based methodologies. Diagnosing a tumor hidden in tissue is one such scenario, where the target is found in a medium consisting of scattering and absorption substances.

1.3 Objectives of the Study

a) To explore the potential of Multispectral, Multifusion Polarimetric Imaging

principles by developing a preclinical optical phantom that represents tumor in a

human tissue. Refractive index variations of the materials in the phantom were

used in the study to represent a tumor in the tissue.

b) To design an effective optical imaging system with fewer instrumentation errors.

c) To apply high efficiency polarimetric imaging techniques using a rotating retarder

and laser light of two different wavelengths.

d) To obtain a better quality image in terms of contrast, that can be effectively used

for optical tumor phantom study.

1.4 Research Hypothesis

a) Subtracted DOLP image provides better contrast than the single DOLP image.

{Subtracted DOLP = (single DOLP) λ1 -(single DOLP) λ2 } 1.1

where λ1 and λ2 are two different wavelengths

b) Contrast of the images changes with different kind of targets

1.5 Limitations of the Study

a) The imaging experiments were done on preclinical phantoms with solutions that

were only similar to the tumor tissue but not an exact replica.

b) Polystyrene of spherical shape was used in the phantom to mimic a tumor.

Substances with other shapes were not used.

c) Only two wavelengths, 633nm and 785nm were used.

CHAPTER II

LITERATURE REVIEW

2.1 Optical imaging techniques using polarization

In the recent years, there has been considerable amount of interest in applying polarization properties of light to biomedical imaging techniques. A few of the studies that used polarization principles for biomedical imaging were discussed in the following section.

Demos, et al [14] demonstrated techniques involving polarization principles for noninvasive surface and beneath-the-surface imaging of biological systems [15]. Spectral and polarization discrimination of the backscattered photons were efficiently used by means of a non-rotating retarder polarimetric configuration to enhance the visibility of the subsurface structures.

Jacques et al [16] used the principles of polarization for examining superficial tissue layers such as skin. The study details the transition of linearly polarized light into randomly polarized light during the light propagation through tissues. Results from the study suggests that polarized light imaging of skin yields images based on photons backscattered from superficial epidermal and initial papillary dermis because birefringent dermal collagen rapidly randomizes polarized light.

Sankaran et al [17] demonstrated the changes in the properties of polarization as light propagates through tissue phantoms with densely packed scatterers. Polystyrene microspheres suspended in aqueous solution were used to study the increase and decrease in linear and circular polarization. This study was vital in designing and optimizing polarimetric techniques for tissue imaging and diagnostics.

Shamaraj Firdous et al [18] demonstrated an analytical model and material characterization technique for the study of scattered polarized light from highly scattering media. This study was useful in understanding the techniques for imaging tissues and hidden objects, which can be, used for diagnostic and treatment modalities of malignant diseases.

Anderson et al [19] demonstrated the use of reflection of polarized light to image tissues such as skin. The components of the reflected light from the skin contained information regarding the structure of the tissue. This paper demonstrates the discrimination of two components of tissue reflectance by viewing the skin through a linear polarizer, under linearly polarized illumination.

2.2 Optical imaging techniques based on Mueller matrix formalism

Bueno [20], in his research presented the indices of linear polarization for an optical imaging system that were calculated using the concept of degree of linear polarization for the light beam emerging from the system. The indices of linear polarization were also expressed as a function of the elements of the corresponding

Mueller matrix.

Nezhuvingal et al [13] demonstrated the use of a Mueller matrix based optical imaging system with application to tissue diagnostics. Smith performed an optimization of a dual-rotating-retarder Mueller matrix polarimeter in his work [21]. Baba et al [22] demonstrated the development and calibration of an automated Mueller matrix polarization imaging system for accurate and noninvasive skin cancer detection.

2.3 Image subtraction techniques

Literature review revealed that the dual energy subtraction technique has been employed in X-ray imaging [23]. Two X-ray sources, one with higher energy and the other with lower energy were used to obtain images of a tissue. A weighted subtraction of the two images produced a digital image that eliminated interfering background structures. Simplification of the background structure in this way increased the detectability of the target structure. Giakos [24]-[26] introduced the dual-energy, multimedia, multidensity sensor that used the principles of dual energy subtraction. The experimental results from this technique indicated that the detector had high signal-to- noise ratio.

Demos et al [15] demonstrated the use of dual-energy techniques in optical imaging. Four different wavelengths (600nm, 690nm, 770nm and 970nm) were used to capture the image of the tissue. Individual images were then compared with the subtracted images (970nm-770nm, 770nm-690nm and 690nm-600nm) to obtain information about objects located at different depths inside the tissue.

2.4 Optical properties of biological tissues

Laser applications in medical imaging requires a thorough knowledge of various optical properties such as absorption coefficient, scattering coefficient, and scattering phase function of the biological tissues and the abnormalities that occur in them. In-vitro phantoms of the abnormalities in tissue can be designed only with a complete knowledge of the various properties of the biological tissue. Some of the research papers that deal with the optical properties of the tissue are discussed below.

Cheong et al [27] reviewed the optical properties of various biological tissues at various wavelengths. Optical properties such as absorption, scattering, total attenuation, and effective attenuation for various biological tissues like aorta, liver and muscle were reviewed in the study. The knowledge about the optical properties of tissue is very important in the design of optical phantoms for tissue optic studies.

Prahl et al [28] described a practical way of determining the optical properties

(scattering, absorption and scattering anisotropy) of a slab of turbid material using total reflection, unscattered transmission and total transmission measurements. The optical properties were obtained by iterating an adding-doubling solution of the radiative transport equation until the calculated values of the reflection and transmission match the measured ones.

Joseph and Gitesh [29] have introduced a micro-optical model that explains most of the observed scattering properties of the biological tissue. Observations from this study showed that the micro-optical model developed represented a tissue best, by a volume of scatterers with a wide distribution of sizes.

CHAPTER III

THEORY

3.1 Laser interaction with tissue

The interaction of laser light with tissue depends upon its optical properties such as refractive index, scattering coefficient and absorption coefficient [18]. When laser interacts with the tissue, it is either absorbed or scattered. Diagnostic applications using laser light are mainly based on the scattered light from the tissue. In a tissue, absorption is mainly due to the presence of tissue chromophores. Also the hemoglobin molecule enclosed in the red blood cells contributes significantly to the absorption process. On the other hand, scattering of light is induced by the refractive index variations of the tissue.

Thus, the light scattering properties are attributed to the morphological structure of the tissue, cell shapes and organelle content which affect the refractive index of the tissue

[30]. Figure 3.1 shows the path traced by light when it interacts with the tissue.

Figure 3.1: Paths traced by light in a tissue 10

In the figure, strongly scattered light is the ray of light that has undergone multiple scattering inside the tissue. Strongly scattered light travels the longest path before reaching the detector. Weakly scatted light is the one that propagates the shortest distance between the object (target) and the detector. The light that has undergone weak scattering inside the tissue contributes to a sharp image of the target inside the tissue and the light that has undergone strong scattering contributes to the diffuse background (tissue).

Diagnostic applications like optical imaging are mainly based on the image formed by the scattered light from the target [31]. When the target is a tissue (scattering / absorption media), the efficiency of an optical imaging technique relies mainly on the quality of image obtained. Strongly scattered light from the tissue loses important structural information about the target (tumor) in the tissue and contributes mainly to the diffuse background seen on the image while the weakly scattered light contributes to a sharp image of the target (tumor) in the tissue. Weakly scattered light retains its incident polarization where as the diffuse scattered light (strongly scattered light) carries a random polarization state. This attributes to the amount of information present in the two types of scattered light. The discrimination of these two kinds of scattered light results in an image with clear depiction of the target against the tissue [7].

3.2 Polarized light

In a transverse electromagnetic wave (light), the waves vibrate in a direction perpendicular to their direction of propagation. Polarization of light is defined as the orientation of the vibration pattern of light in a single plane. In other words it is the restriction of the vibrations of electric or magnetic field vector to a single plane. An

unpolarized light is one which has vibrations in all possible directions. Linear and circular polarized light were used in the experiment procedure. A plane electromagnetic wave is said to be linearly polarized. Linear polarization is illustrated in the Figure 3.2.

Figure 3.2: Linearly polarized light

A light wave with two perpendicular electromagnetic plane waves of equal

amplitude and 90° difference in phase defines circularly polarized light. Figure 3.3

illustrates a circularly polarized light.

Figure 3.3: Circularly polarized light

3.3 Multispectral imaging

The performance of optical imaging in tissues relies on the nature of the light used.

Laser light with different wavelengths have different photon energy and it is calculated as shown below.

E = hc / λ 3.1 where h is the Plancks constant, c is the velocity of light in vacuum in m/s and λ is the wavelength of light in meters. The interaction of light with a medium varies with the wavelength due to the difference in photon energies. Thus, photons with different energy carry different information about the medium. The difference between images obtained using light sources of different wavelengths may not be visible to the naked eye.

However, subtraction of an image obtained with light source of one wavelength from another image obtained with light source of a different wavelength reveals information about the medium, which is hidden in each of the individual images [15]. Hence, in the experimental procedure of this research study, two lasers were used, one in the visible range (633nm) while the other in the near-infrared range (785nm).

3.4 Polarimetric imaging

Polarimetry is the science of measuring polarization. Interaction of polarized light with the target always results in changing the state of polarization of the interacting light.

Weakly scattered light retains its polarization state while strongly scattered light does not retain its polarization state [9]. Interrogating the state of polarization of laser light transmitted through the target results in a better imaging procedure to extract useful information from the target [31].

3.5 Stokes parameter

The polarization state of light can be effectively represented by the four Stokes parameters [32] as shown below.

2 2 S0 = E x + E y 3.2

2 2 S1 = E x - E y 3.3

S2 = 2 E x Ey Cos δ 3.4

S3 = 2 E x E y Sin δ 3.5 where E x and E y represent the maximum amplitudes of the optical field components in x and y direction respectively and δ represents the phase difference between the optical field components.

S0 describes the total intensity of light

S1 describes the amount of linear horizontal or vertical polarization

S2 describes the amount of linear +45 ° or -45 ° polarization

S3 describes the amount of right or left circular polarization contained in the light beam

3.6 Mueller matrix

The polarization state of a light beam changes when it comes in contact with a medium, that is, the incident beam and the exiting beam will have different states of

polarization. If Si , for i = 0,1,2,3 represents the Stokes parameters of the incident beam

' and Si for i = 0,1,2,3 represents the Stokes parameters of the exiting beam, then each of the polarization parameters can be expressed as a linear combination of the parameters

Si of the incident beam. This relationship in a matrix form is shown below

 S '  m m m m  S   0   00 01 02 03  0  '  S   m10 m11 m12 m13  S1  1 = 3.6  S '  m m m m S   2   20 21 22 23  2   '      S3  m30 m31 m32 m34  S3 

The above matrix form can be expressed as a matrix equation as shown below

[S ' ]= [M ][S] 3.7

The 4*4 matrix in equation 3.6 is known as the Mueller matrix. The elements of the

Mueller matrix represent the optical polarization properties of the medium. The property of the medium that alters polarization of the light beam is completely defined by the

Mueller matrix [32]. Thus, Mueller matrix is a mathematical representation of the optical polarization properties of a medium.

3.7 Multispectral Polarimetric imaging

Giakos [10] [11] proposed the technique of multispectral polarimetric imaging. This technique involves the use of different wavelengths for polarimetric imaging of the target. This technique is used in this research study for enhanced tumor detection. In general, multiple wavelengths can be utilized to interrogate the target. As a result, exploration and arithmetic manipulation of the different Stokes parameters, obtained at different wavelengths using subtraction, addition, multiplication, division or combination of them, can enhance the image. The multispectral polarimetric image differences obtained through multi wavelength (λ1, λ2) interrogation of light can be expressed as follows.

(DOP) λ1 -(DOP) λ2 3.8

(DOLP) λ1 -(DOLP) λ2 3.9 15

(DOCP) λ1-(DOCP)λ2 3.10

(e) λ1-(e) λ2 3.11

(η) λ1 - (η) λ2 3.12

(ε) λ2 -(ε) λ1 3.13 where, the degree of polarization (DOP), degree of linear polarization (DOLP), degree of circular polarization (DOCP), ellipticity, and orientation can also be estimated in terms of

Stokes parameters, as

(S 2 + S 2 + S 2 ) 2/1 DOP = 1 2 3 3.14 S0

(S 2 + S 2 ) 2/1 DOLP = 1 2 3.15 S0

S DOCP = 3 3.16 S0

b s e = = 3 3.17 a 2 2 s0 + s1 + s2

1 s η = arctan[ 2 ] 3.18 2 s1

ε = 1 − e2 3.19 where S 0, S 1, S 2, S 3 are the Stokes vectors, e, η, and ε are the ellipticity, azimuth, and eccentricity, respectively. The Muller-based polarimetric images, should exhibit superior imaging characteristics, due to the complete polarimetric description of the target [12].

CHAPTER IV

EXPERIMENTAL SETUP AND PROCEDURES

4.1 Preclinical Phantom Design

Ideally, the potential of an imaging technique could be explored with tissue extracted through biopsy. However, the constraints and limitations associated with the use of actual tumor tissue makes it almost impossible to use them in tumor detection studies. It is also very difficult to maintain actual tumor tissue samples over the course of the experiment. All these disadvantages of the actual tumor tissue lead to the use of preclinical phantoms in tumor detection studies.

A preclinical phantom emulating a tumor present in the human tissue was designed.

Specifically a small polystyrene sphere of diameter 3mm embedded in a water-milk / water-intralipid-ink solution was utilized. This polystyrene sphere was glued to a straw and then fixed to the bottom of the test tube. The gap between the surface of the polystyrene sphere and the wall of the test tube was 1 mm. In order to depict a tissue with tumor, solutions that have close relation to the optical properties of a human tissue were used inside the test tube.

Intralipid is a liquid that is normally used as intravenous nutrition for patients who cannot digest ordinary food. It is often used as a tissue phantom in tissue optics experiments because of its light scattering properties and its ease of use [33] [34].

Intralipid is similar to milk and the scattering occurs due to the small (lipid) particles

suspended in the water. While scattering property of a tissue was simulated by skim milk

[35] and intralipid solution, the absorptive property of the tissue was simulated by the use of ink solution [36]. Figure 4.1 shows the preclinical phantom used in the experiment.

The following solutions were placed inside the test tube.

a) 9ml of water with 1.2 ml of skim milk.

b) 9ml of water with 0.1 ml of 4 % blue ink solution and 0.1 ml of 1 % intralipid

solution.

Figure 4.1: Phantom for tissue infected with tumor

4.2 Experimental Setup

The imaging system presented in this study was operated using backscatter geometry. The experimental setup is shown in Figure 4.2. The equipment used in the experimental setup is discussed in Chapter V. Multispectral imaging was carried out in the experiments by using two different lasers namely, a Helium-Neon laser (633nm) and a near-infrared laser (785nm) in the same experimental setup. The setup had two linear polarizers and two quarter wave retarders. A beam expander was used to magnify the laser beam illuminating the optical tumor phantom. Frosted glass (23653, Altuglas

International Mexico, Inc., Brownsville, TX) was used to reduce the intensity of the laser beam, as well as, to remove the speckles from the laser beam. A CCD camera interfaced with the computer was used to capture the images of the target with the help of image processing software (V ++ Precision Digital Imaging System, Digital Optics Ltd.,

Auckland, New Zealand).

Figure 4.2: The experimental Setup 19

4.3 Experimental Procedure

The linear polarizers in the setup were aligned parallel to each other throughout the course of the experiment. Parallel setup was used in order to have maximum intensity of light incident on the target, as well as, the detector. The retarder on the transmitter side was used to convert linearly polarized light to circularly polarized light. The retarder used in the receiver side was varied from 0° to 157.5° in steps of 22.5°. This retarder changed the circularly polarized light back to a linear polarized light, which then passed through the linear polarizer and the CCD camera. For each angular setting of the retarder in the receiver side, an image was recorded using the imaging system, so that a total of eight images were obtained for the rotating retarder (receiver side) setup. These eight images were then used to calculate the Stokes parameters of the reflected light. DOLP was then calculated from the Stokes parameters. A Helium-Neon laser was first used in the setup and eight images of the optical phantom were taken. The Helium-Neon laser was then replaced by a near-infrared laser and another set of eight images were recorded for the same optical phantom. First, 9ml of water with 1.2 ml of skim milk was used in the phantom and the DOLP image was taken for each of the wavelengths. Second, 9ml of water with 0.1 ml of 4 % blue ink solution and 0.1 ml of 1% intralipid solution was used in the phantom and DOLP image were taken for each of the wavelengths.

4.4 Alignment and Calibration Procedures

All the optical components used in the imaging system were placed in fixed locations using rigid mounts. This was necessary to reduce errors caused due to change in position of the optical components during the course of the experiment. Lasers used in the system were aligned using optical components present in the transmitter side of the setup. Since two lasers were used in the experiment, several factors were considered for precise imaging. Intensity of light incident on the phantom was kept constant for both lasers with the help of power alignment screws present at the back of the laser. Distances between the optical components were kept constant during experiments. This ensured that the image profile (magnification and the relative pixel position) remained the same for all the images. This was necessary for the purpose of image subtraction.

The CCD camera used for imaging had three set of alignment screws; magnification, sharpness and slit opening. A sheet of printed paper was used as a target for calibrating the camera. With the help of a table lamp source, the three alignments screws were adjusted till the printed letters appeared clear and sharp on the computer to which the camera was interfaced. After this step, the optical tumor phantom was kept in place and the alignments screws were once again adjusted to obtain the best possible image of the phantom. The alignment screws were held in this position The Stokes parameter images of a white paper were then obtained by eight images taken of the white paper with the rotating retarder and the data reduction algorithm and checked for uniform illumination.

4.5 Data Reduction Algorithm

The DOLP algorithm was based on the polarimetric data measurement matrix formalism [8] developed by Chenault and Pezzaniti. The polarimetric measurement matrix reduced the data to a sequence of matrix manipulations. Following this treatment, the Stokes vector incident on the detector was expressed as

' S = AS inc 4.1

T where S inc = (s0 s1 s2 s3 ) is the Stokes vector incident on the polarization state analyzer and A is the Mueller matrix that describes both the elements of the polarization state analyzer and instrumental polarization between the polarization state analyzer and

the detector. An analyzer vector, A = (a0 a1 a2 a3 ), was formed analogous to the

Stokes vector and was used to calculate the intensity of the light beam falling on the detector using the dot product equation as shown below.

i = A • S inc = a0 s0 + a1s1 + a2 s2 + a3 s3 4.2 where i is the intensity of the light beam falling on the detector.

The incident Stokes vector S inc was determined by making a series of measurements iq , changing the elements of the polarization state analyzer for each measurement. The intensity of the q th measurement was then calculated as shown below.

iq = Aq • S inc 4.3

th where Aq is the analyzer vector for the q measurement. The expression for Q measurements was then conveniently expressed as

 i   a a a a   0   00 01 02 03   i1   a10 a11 a12 a13  S0       . .  S1    =   4.4  .   . S   2   .   .       S3      iQ−1  a(Q− 0)1 a(Q− 1)1 a(Q− 2)1 a(Q− 3)1 

th th where aqj is j ( j = 3,2,1,0 ) element for the q measurement. The above equation 4.4 was rewritten as,

I q = W S inc 4.5 where W is the polarimetric measurement matrix.

If the polarimetric measurement matrix was known, then the calculated Stokes vector R can be found from the inverse of that matrix and the measured intensities by the polarimetric data reduction equation shown below.

R = W −1 I + U I 4.6 where U is the polarimetric data reduction matrix. For more than four measurements, W is not square and the pseudo inverse was used. If the retarder was quarter wave, then the

Mueller calculation equation is given by,

' S = M p M r (θ q )S inc 4.7

 s '  1 1 0 01 0 0 0  s   0     0  ' 0 cos 2 2θ cos 2θ sin 2θ − sin 2θ  s1  1 1 1 0 0 q q q q  s1   '  =  2  4.8 s 2 0 0 0 0 0 cos 2θ sin 2θ sin 2θ cos 2θ s   2    q q q q  2   '  0 0 0 00 sin 2θ − cos 2θ 0  s   s3    q q  3 

1 cos 2 2θ cos 2θ sin 2θ − sin 2θ  s   q q q q  0  2 1 1 cos 2θ cos 2θ sin 2θ − sin 2θ  s1  = q q q q 2 0 0 0 0  s    2     0 0 0 0  s3 

When Q = 8 and a measurement was made every 22.5° from 0° to 157.5°, then the polarimetric measurement equation is given by,

i  1 1 0 0   0    i1  1 5.0 5.0 −1 2  i  1 0 0 −1 s   2    0  i3  1 5.0 − 5.0 −1 2  s1  I =   = 4.9 i 1 1 0 0 s   4    2      i5 1 5.0 5.0 1 2  s3      i6  1 0 0 1      i7  1 5.0 − 5.0 1 2 

The Stokes vector R was then calculated by the equation shown below.

r   0   r1  −1 R = = ()W TW W T I = U I 4.10 r   2     r3 

The values of the polarimetric data reduction matrix U is shown below.

− .0 25 .0 25 .0 75 .0 25 .0 25 .0 25 .0 75 .0 25     1 0 −1 1 1 0 −1 0  U = 4.11  0 1 0 0 0 0 0 −1       0 − 2 4 − 5.0 − 2 4 0 − 2 4 5.0 − 2 4 

Finally the degree of linear polarization was calculated from the output Stokes parameters using the formula,

S 2 + S 2 DOLP = 1 2 4.12 S0 where S 0, S 1, S 2 are the Stokes parameters. The parameter S 0 describes the total intensity of light. The parameter S 1 describes the amount of linear horizontal or vertical polarization .The parameter S 2 describes the amount of linear +45 ° or -45 ° polarization.

4.6 Analysis Technique

Contrast values were used to assess the quality of an image. The DOLP images obtained for each of the target using different wavelengths have different image contrast and quality. The Signal-to-Background ratio was used as a measure of image contrast.

For its calculation, average intensity of 100 pixel points over the region of interest was calculated. 100 pixel points on a horizontal line were able to cover the entire diameter of the polystyrene sphere region in the image. Since each of the individual DOLP images, as well as, the subtracted DOLP images had the same image profile, the horizontal and vertical coordinate axes in the images were used to make sure that the same 100 pixels points were chosen in each of the images. An intensity graph was then plotted for the pixel points and the intensity value using a row plot command in V++ image processing software. The intensity graph obtained from the V++ image processing software was then used in Microsoft Excel to get the average intensity values of the 100 pixel points inside the polystyrene sphere, as well as, the average intensity values of the 100 pixel points outside the polystyrene sphere. The region inside the polystyrene sphere was considered as the signal and the region outside the polystyrene sphere was considered as the

background. These average intensity values of the signal and the background were then used in the equation shown below to calculate the Signal-to-Background ratio.

b - s - b Signal-to-Background ratio = 4.13 1 s( + )b 2 where s is the average intensity of the signal and b is the average intensity of the background.

CHAPTER V

MATERIALS

5.1 Optical Tabletop

A suitable tabletop is required to carry out the optical experiments with precision because even the slightest of misalignment in height or position of the optical components would result in a major performance drop of the experiments being performed. An optical tabletop (StableTop™, Melles Griot, Carlsbad, CA) design shown in Figure 5.1 was used for mounting all the optical components used in the experiment.

Figure 5.1: The Melles Griot StableTop™ tabletop with triple-plate, double- honeycomb-core construction includes TurboClean™ sealed mounting holes

5.2 Lasers

Lasers were used in the experiments to illuminate the optical tumor tissue phantom.

A semiconductor laser (633nm) and an infrared laser (785nm) were used in the experimental setup.

5.2.1 Semiconductor laser

A red Helium-Neon laser (1135P, JDS Uniphase, San Jose, CA) of 633nm wavelength was used in the experiment. It offers high power stability and low noise.

The specifications of the 1135P model Helium-Neon laser is shown in Table 5.1

Table 5.1: Specifications of the 1135P JDS Uniphase Helium-Neon laser

Parameter Value

Wavelength 632.8nm

Mode purity > 95nm

Minimum output power 10.0 %

Maximum noise 1.0 %

Operating voltage 3100 V DC

Operating current 6.5 mA

5.2.2 Infrared Laser

IR Laser system (IS785-25, Intelite, Inc., Minden, NV) of 785nm wavelength was used in the experiment. The specifications of the IR Laser system is shown in Table 5.2

Table 5.2: Specifications of the IS785-25 model, IR Laser system

Parameter Value

Type/Mode Continuous Wave / Single mode

Wavelength 785nm

Laser Diode output power 25 mW

Laser head size 45 * 60 * 120 mm

Power stability < 5 %

Operating voltage 5 VDC / Maximum 350 mA

Power supply input 100 – 240 VAC, 50 – 60 Hz

Power supply output 5 VDC, Maximum 1.6 A

5.3 Linear Polarizer

Two Dichroic sheet polarizers (FPG 001, Melles Griot, Rochester, NY) were used in the experiments. They were made of a plastic dichroic sheet sandwiched between selected strain-free glass plates. Dichroic sheet polarizer offers large apertures and acceptance angles.

5.4 Retarder

A quarter wave quartz retardation plate (WRM 003, Melles Griot, Rochester, NY) was used as a rotating retarder in the analyzer side of the experimental setup and a Berek compensator (5540, New Focus Inc., San Jose, CA) was used as another quarter wave retarder in the transmitter side of the experimental setup

5.4.1 Berek compensator

The Berek compensator is a variable wave plate and it can be used as both quarter wave and half wave retardation plate at any wavelength between 200nm and 1600nm.

Figure 5.2 shows the model 5540 Berek compensator and figure 5.3 shows the various alignment screws available in the compensator.

Figure 5.2: Berek compensator

Figure 5.3: Side view of Berek compensator showing various alignment screws

Quarter wave retardation for a particular wavelength can be achieved by the use of following equation.

−1 θ R = sin .0( 284 λR) 5.1

where θR is the tilt angle, R is the retardance in waves and λ is the wavelength in microns.

 π  I = 50.22 − 71sin −θ R  5.2  4  where I is the retardation indicator setting.

5.5 Beam Expander

A beam expander (NT55-579, Edmund Optics Inc., Barrington, NJ, USA) was used in the experiment to magnify the laser beam that is illuminating the tumor tissue phantom. The region of interest in the target was illuminated with an expanded laser beam by the use of the beam expander. Table 5.3 shows the specifications for the beam expander.

Table 5.3: Specifications for the beam expander

Beam Expansion Power 5X, 10X, 20X

Entrance aperture 2.0 mm, maximum

Exit aperture 27 mm maximum

Focus Range 1.2m to infinity

Construction Black Anodized Aluminum

5.6 CCD Camera

A Photometric SenSys (1401E, Roper Scientific Inc., Tucson, AZ) high resolution digital camera system was used as the detector system in the experimental setup. This cooled CCD camera system provides 12 bit digitization. Table 5.4 shows the specification of the camera.

Table 5.4: Specifications for the CCD Camera

CCD image sensor Kodak KAF 1401E; scientific grade

CCD Format 1317 * 1035 imaging pixels; 9.0 * 7.0 mm imaging area Nonlinearity ≤ 0.5 %

Readout bits/speed 12 bits @ 1.4 MHz

Frame readout 1.39 seconds for full frame

Operating environment 0 to 40˚ C ambient, 0 to 70 % relative humidity

5.7 Polystyrene sphere

A white polystyrene sphere (Polysciences Inc., Warrington, PA) was used to mimic tumor in the optical tumor tissue phantom. The diameter of the polystyrene sphere used was 3 mm and the refractive index of the sphere was 1.6.

5.8 Intralipid

Intralipid (Sigma-Aldrich Co., St. Louis, MO) was used in the phantom to mimic the scattering property of the tissue. Intralipid had Phospholipid stabilized soybean oil with

20 % fat emulsion. 32

Figure 5.4 and figure 5.5 shows the experimental setup using semiconductor laser and the near-infrared laser respectively and figure 5.9 shows the optical phantom used in the experiment.

Figure 5.4: Photograph of the experimental setup with semiconductor laser

Figure 5.5: Photograph of the experimental setup with near-infrared laser

Figure 5.6: Photograph of the preclinical phantom used in the experiment

CHAPTER VI

RESULTS AND DISCUSSION

6.1 Single DOLP images

Images of the polystyrene sphere embedded in the following solutions,

a) Solution 1: 9ml of water with 1.2 ml of skim milk

b) Solution 2: 9ml of water with 0.1 ml of 4 % blue ink solution and 0.1 ml

of 1 % intralipid solution were taken at 633nm and 785nm respectively using the experimental setup shown in

Figure 4.2. The polarimetric imaging technique using rotating retarder backscatter geometry was employed in obtaining the images. The images obtained from each of the solutions using a particular wavelength were used in the data reduction algorithm and a single DOLP image was obtained. The single DOLP images and their corresponding intensity plots for each of the different solution for a particular wavelength are shown in the following figures.

Figures 6.1, 6.2 and 6.3 shows the single DOLP image of the polystyrene sphere embedded in solution 1 obtained using 633nm laser, the intensity graph plotted for 100 horizontal pixel points inside the polystyrene sphere of the DOLP image and the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the DOLP image respectively. The intensity plots were used to calculate the average intensity values. The signal-to-background contrast ratio was then calculated from the average

intensity values of the signal (region of the image inside the polystyrene sphere) and the background (region of the image outside the polystyrene sphere).

Figures 6.4, 6.5 and 6.6 shows the single DOLP image of the polystyrene sphere embedded in solution 1 obtained using 785nm laser, the intensity graph plotted for 100 horizontal pixel points inside the polystyrene sphere of the DOLP image and the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the DOLP image respectively.

Figures 6.7, 6.8 and 6.9 shows the single DOLP image of the polystyrene sphere embedded in solution 2 obtained using 633nm laser, the intensity graph plotted for 100 horizontal pixel points inside the polystyrene sphere of the DOLP image and the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the DOLP image respectively.

Figures 6.10, 6.11 and 6.12 shows the single DOLP image of the polystyrene sphere embedded in solution 2 obtained using 785nm laser, the intensity graph plotted for

100 horizontal pixel points inside the polystyrene sphere of the DOLP image and the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the DOLP image respectively.

6.2 Back-Scattered Mode Single DOLP images and their intensity plots

Figure 6.1: DOLP for solution 1 (633nm)

Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel 6

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.2: Intensity plot for the region within the polystyrene sphere (solution 1)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.3: Intensity plot for the region outside the polystyrene sphere (solution 1)

Figure 6.4: DOLP for solution 1 (785nm)

Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel 6

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.5: Intensity plot for the region within the polystyrene sphere (solution 1)

4 Pixel Intensity (Arbitrary units) (Arbitrary Pixel Intensity

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x )

Figure 6.6: Intensity plot for the region outside the polystyrene sphere (solution 1) 39

Figure 6.7: DOLP for solution 2 (633nm)

15 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.8: Intensity plot for the region within the polystyrene sphere (solution 2)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.9: Intensity plot for the region outside the polystyrene sphere (solution 2)

Figure 6.10: DOLP for solution 2 (785nm)

20 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.11: Intensity plot for the region within the polystyrene sphere (solution 2)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.12: Intensity plot for the region outside the polystyrene sphere (solution 2) 42

6.3 Inferences from single DOLP images

As already mentioned in the introduction, different wavelength lasers interact differently, via absorption, scattering, and reflection. This fact was very much evident from the DOLP images of the optical tumor phantom obtained using the two laser sources. The near-infrared laser (785nm) provided a DOLP image with better visualization of the polystyrene sphere in both solution 1 and solution 2 compared to the semiconductor laser. Figures 6.4 and 6.10 have better clarity in depicting the polystyrene sphere compared to the Figures 6.1 and 6.7 respectively. This is because, the infrared laser beam had undergone less scattering compared to the 633nm laser, after interacting with the polystyrene sphere embedded in the phantom.

Solution 2 in the phantom was able to provide images that had better depiction of the polystyrene sphere against the background compared to solution1. Solution 2 had both scattering and absorption substances to mimic a tissue whereas solution 1 had scattering substances alone. The refractive indices of some of the biological tissues (chicken liver, porcine adipose tissue and human tissue samples from liver, kidney, skin and myocardium) were in the range of 1.3 to 1.5 [37] [38]. The skim milk has a refractive index close to 1.462 [39] and the intralipid solution has a refractive index close to 1.33

[37]. Since the polystyrene sphere (refractive index is 1.6) had a refractive index different from the water/milk and water-intralipid-ink solution, the polystyrene sphere was chosen to represent a tumor in the phantom. This difference in refractive index of the object of interest and the background was essential in this tumor phantom study. These results indicate that a correct amount of scattering and absorption substances in the optical

phantom to emulate a tissue could result in a optical imaging system that can effectively discriminate between the object of interest against the background.

6.4 Subtracted DOLP images

The single DOLP images obtained at different wavelengths were subtracted in the following order to obtain the subtracted DOLP images.

a) Subtracted DOLP image(633-785) = DOLP 633nm - DOLP 785nm

b) Subtracted DOLP image(785-633) = DOLP 785nm - DOLP 633nm

The subtracted DOLP images for solution 1 and solution 2 and their corresponding intensity plots were presented in the following figures.

Figures 6.13, 6.14 and 6.15 shows the subtracted DOLP image(633nm-785nm) of the polystyrene sphere embedded in solution 1, the intensity graph plotted for 100 horizontal pixel points inside the polystyrene sphere of the subtracted DOLP image and the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the subtracted DOLP image respectively.

Figures 6.16, 6.17 and 6.18 shows the subtracted DOLP image(785nm-633nm) of the polystyrene sphere embedded in solution 1, the intensity graph plotted for 100 horizontal pixel points inside the polystyrene sphere of the subtracted DOLP image and the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the subtracted DOLP image respectively.

Figures 6.19, 6.20 and 6.21 shows the subtracted DOLP image(633nm-785nm) of the polystyrene sphere embedded in solution 2, the intensity graph plotted for 100 horizontal pixel points inside the polystyrene sphere of the subtracted DOLP image and

the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the subtracted DOLP image respectively.

Figures 6.22, 6.23 and 6.24 shows the subtracted DOLP image(785nm -633nm) of the polystyrene sphere embedded in solution 2, the intensity graph plotted for 100 horizontal pixel points inside the polystyrene sphere of the subtracted DOLP image and the intensity graph plotted for 100 horizontal pixel points outside the polystyrene sphere of the subtracted DOLP image respectively.

6.5 Subtracted DOLP images and their intensity plots

Figure 6.13: Subtracted DOLP for solution 1 (633nm-785nm)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.14: Intensity plot for the region within the polystyrene sphere (solution 1)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel 4

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.15: Intensity plot for the region outside the polystyrene sphere (solution 1)

Figure 6.16: Subtracted DOLP for solution 1 (785nm-633nm)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.17: Intensity plot for the region within the polystyrene sphere (solution 1)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel 4

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.18: Intensity plot for the region outside the polystyrene sphere (solution 1) 48

Figure 6.19: Subtracted DOLP for solution 2 (633nm-785nm)

10 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.20: Intensity plot for the region within the polystyrene sphere (solution 2)

6 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel 4

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.21: Intensity plot for the region outside the polystyrene sphere (solution 2)

Figure 6.22: Subtracted DOLP for solution 2 (785nm-633nm)

20 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.23: Intensity plot for the region within the polystyrene sphere (solution 2)

4 Pixel Intensity (Arbitrary units) Intensity (Arbitrary Pixel

0 0 10 20 30 40 50 60 70 80 90 100 Horizontal Pixel Postion (x)

Figure 6.24: Intensity plot for the region outside the polystyrene sphere (solution 2) 51

6.6 Inferences from subtracted DOLP images

The inferences from section 6.3 clearly indicated the efficiency of the polarimetric imaging system in detecting the polystyrene sphere against the background in the optical tumor phantom. However, the process of subtracting the individual DOLP images obtained from two different wavelengths provided an image with better visualization of the polystyrene sphere against the background. This was evident from the subtracted

DOLP images shown in the figures listed in section 6.5.

During interrogation of the phantom, 785nm laser had greater penetration power over the solution present in the phantom to effectively reach the polystyrene sphere and the reflected light from the polystyrene sphere suffered least scattering before reaching the CCD Camera while the 633nm laser was not able pass over the solution to reach the polystyrene sphere due to its low penetration power. These effects attributed to the amount of information present in the images obtained using the two wavelengths. The

785nm laser was able to provide better information about the polystyrene sphere and had a greater depth profile. The 633nm laser was able to provide more information about the background than the sphere and had a lesser depth profile. When the DOLP image from

633nm laser was subtracted from the DOLP image of 785nm laser, a lesser depth profile information was subtracted from greater depth profile information. The discrimination of the polystyrene sphere from the background became much easier in the subtracted DOLP images compared to the individual DOLP images obtained at different wavelengths.

However the other way of subtraction (633nm-785nm) did not work as good as the earlier one. These inferences were very much evident from the images shown in the figures.

Figures 6.16 and 6.22 were clear in depicting the polystyrene sphere against the

background compared to Figures 6.13 and 6.19 respectively. Until now, all the inferences were made only on visualizing the images by naked eye.

6.7 Intensity measurements of the signal and the background and inferences

Tables 6.1 and 6.2 shows the average intensity value measurements for the signal and the background that were calculated from a total of 100 pixel points from the DOLP images for solution1 and solution 2 respectively.

Table 6.1: Average intensity value measurements of the signal and the background for solution 1 DOLP Images Average intensity Average intensity of the signal of the background (Arbitrary units) (Arbitrary units) Single DOLP (633nm) 6.32 8.4

Single DOLP (785nm) 7.66 4.34

Subtracted DOLP(633nm-785nm) 1.64 2.67

Subtracted DOLP (785nm-633nm) 2.98 1.39

Table 6.2: Average intensity value measurements of the signal and the background for solution 2 DOLP Images Average intensity Average intensity of the signal of the background (Arbitrary units) (Arbitrary units) Single DOLP (633nm) 9.93 4.84

Single DOLP (785nm) 16.39 6.21

Subtracted DOLP (633nm-785nm) 2.1 0.99

Subtracted DOLP (785nm-633nm) 8.56 2.36

Table 6.1 shows that the average intensity value of the signal for 785nm laser was much higher than the average intensity value of the background for a single DOLP image obtained from solution 1. However for the 633nm laser, the average intensity value of the background was higher than the average intensity value of the signal. This clearly indicated that the 785nm laser was able to effectively reach the polystyrene sphere during the interrogation process. This was the reason for better quality DOLP images obtained with 785nm lasers. Table 6.2 also shows that the intensity value of the signal was higher than the background for the single DOLP images obtained from solution 2. This was the reason for the clear depiction of the polystyrene sphere in solution 2 by both the lasers.

Again, the subtracted DOLP images, especially the 785nm-633nm DOLP image had higher average intensity values for the signal compared to the background in both the solutions.

6.8 Signal-to-Background contrast ratio measurements and inferences

Signal-to-Background contrast ratio was calculated using the formula

b - s - b Signal-to-Background ratio = 6.1 1 s( + )b 2 where s is the average intensity of the signal and b is the average intensity of the background

Tables 6.3 and 6.4 indicate the contrast values of different DOLP images for solution 1 and solution 2 respectively.

Table 6.3: Signal-to-Background contrast ratio measurements for solution 1

DOLP Images Contrast ratio values

Single DOLP (633nm) 0.2826

Single DOLP (785nm) 0.5533

Subtracted DOLP (633nm-785nm) 0.4780

Subtracted DOLP (785nm-633nm) 0.7277

Table 6.4: Signal-to-Background contrast ratio measurements for solution 2

DOLP Images Contrast ratio values

Single DOLP (633nm) 0.6892

Single DOLP (785nm) 0.9009

Subtracted DOLP (633nm-785nm) 0.7184

Subtracted DOLP (785nm-633nm) 1.1355

Tables 6.3 and 6.4 clearly indicate that the contrast values of the subtracted DOLP images (785nm-633nm) are much higher than the individual DOLP images. Contrast being a measure of the quality of an image clearly indicated that the subtracted DOLP images provided better information compared to the individual DOLP images in discriminating the polystyrene sphere against the background.

CHAPTER VII

CONCLUSION AND FUTURE WORK

An optical imaging system was successfully designed with precision following a series of calibration and alignment techniques and was used in the optical tumor phantom study. The quality of the DOLP images indicates the efficiency of the image processing algorithm devised. The experimental results and the contrast values clearly indicate that the subtracted DOLP image exhibit a better quality in discriminating the polystyrene sphere against the background compared to the single DOLP images. The results also show that the contrast of the DOLP images was found to vary with the type of solutions used in the phantom. The results can be more appealing if better solutions that mimic the tissue exactly were used in the phantom model. Thus, the optical imaging system utilizing Multispectral Polarimetric Imaging principles has been successful in providing an enhanced image of the optical tumor phantom, describing the structure of the polystyrene sphere hidden in two different kinds of solution.

The exploration of this technique with several other wavelength lasers may lead to an optimized experimental configuration, yielding to further image improvement.

Evaluation of this technique to interrogate actual tumor tissue remains to be done in the future.

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