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Shape/Image Registration for Medical Imaging : Novel Algorithms and Applications

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Shape/Image Registration for Medical Imaging : Novel Algorithms and Applications University of Louisville ThinkIR: The University of Louisville's Institutional Repository Electronic Theses and Dissertations 12-2014 Shape/image registration for medical imaging : novel algorithms and applications. Ahmed Magdy Shalaby 1982- University of Louisville Follow this and additional works at: https://ir.library.louisville.edu/etd Part of the Biomedical Commons, and the Radiology Commons Recommended Citation Shalaby, Ahmed Magdy 1982-, "Shape/image registration for medical imaging : novel algorithms and applications." (2014). Electronic Theses and Dissertations. Paper 1768. https://doi.org/10.18297/etd/1768 This Doctoral Dissertation is brought to you for free and open access by ThinkIR: The University of Louisville's Institutional Repository. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of ThinkIR: The University of Louisville's Institutional Repository. This title appears here courtesy of the author, who has retained all other copyrights. For more information, please contact [email protected]. SHAPE/IMAGE REGISTRATION FOR MEDICAL IMAGING: NOVEL ALGORITHMS AND APPLICATIONS By Ahmed Magdy Shalaby B.Sc. in Electrical Engineering, Alexandria University, 2003 M.Sc. in Electrical Engineering, Alexandria University, 2009 A Dissertation Submitted to the Faculty of the J. B. Speed School of Engineering of the University of Louisville in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Department of Electrical and Computer Engineering University of Louisville Louisville, Kentucky December 2014 i ii SHAPE/IMAGE REGISTRATION FOR MEDICAL IMAGING: NOVEL ALGORITHMS AND APPLICATIONS By Ahmed Magdy Shalaby B.Sc. in Electrical Engineering, Alexandria University, 2003 M.Sc. in Electrical Engineering, Alexandria University, 2009 A Dissertation Approved on November 20, 2014 by the following Dissertation Committee: ________________________________________ Aly A. Farag, Ph.D., Dissertation Director ________________________________________ James Graham, Ph.D. ________________________________________ Tamer Inanc, Ph.D. ________________________________________ R. Todd Hockenbury, M.D. ________________________________________ Chin Ng, Ph.D. ii DEDICATION I would like to dedicate this dissertation to my country “EGYPT” which gave me invaluable educational opportunities, my great mother “GALILA” and my beloved wife “REHAM” for their love and patience. iii ACKNOWLEDGEMENTS First of all, I would like to thank God the merciful, the compassionate for all the blessings and for granting me the opportunity to accomplish my PhD degree successfully. I would like to express my deepest gratitude to my advisor Dr. Aly A. Farag for his guidance, support, and encouragement to pursue a Ph.D. degree in the computer vision and medical imaging field. I would like to acknowledge the other members of my Ph.D. committee for spending time and effort in reading and reviewing my work Dr. James H. Graham, Dr. R. Todd Hockenbury, Dr. Tamer Inanc, and Dr.Chin Ng. Also, I would like to thank to Mr. Mike Miller, and all CVIP Lab members for their friendship and assistance. iv ABSTRACT SHAPE/IMAGE REGISTRATION FOR MEDICAL IMAGING: NOVEL ALGORITHMS AND APPLICATIONS Ahmed M. Shalaby Novmber 20, 2014 This dissertation looks at two different categories of the registration approaches: Shape registration, and Image registration. It also considers the applications of these approaches into the medical imaging field. Shape registration is an important problem in computer vision, computer graphics and medical imaging. It has been handled in different manners in many applications like shape- based segmentation, shape recognition, and tracking. Image registration is the process of overlaying two or more images of the same scene taken at different times, from different viewpoints, and/or by different sensors. Many image processing applications like remote sensing, fusion of medical images, and computer-aided surgery need image registration. This study deals with two different applications in the field of medical image analysis. The first one is related to shape-based segmentation of the human vertebral bodies (VBs). The vertebra consists of the VB, spinous, and other anatomical regions. Spinous pedicles, and ribs should not be included in the bone mineral density (BMD) measurements. The VB segmentation is not an easy task since the ribs have similar gray level information. v This dissertation investigates two different segmentation approaches. Both of them are obeying the variational shape-based segmentation frameworks. The first approach deals with two dimensional (2D) case. This segmentation approach starts with obtaining the initial segmentation using the intensity/spatial interaction models. Then, shape model is registered to the image domain. Finally, the optimal segmentation is obtained using the optimization of an energy functional which integrating the shape model with the intensity information. The second one is a 3D simultaneous segmentation and registration approach. The information of the intensity is handled by embedding a Willmore flow into the level set segmentation framework. Then the shape variations are estimated using a new distance probabilistic model. The experimental results show that the segmentation accuracy of the framework are much higher than other alternatives. Applications on BMD measurements of vertebral body are given to illustrate the accuracy of the proposed segmentation approach. The second application is related to the field of computer-aided surgery, specifically on ankle fusion surgery. The long-term goal of this work is to apply this technique to ankle fusion surgery to determine the proper size and orientation of the screws that are used for fusing the bones together. In addition, we try to localize the best bone region to fix these screws. To achieve these goals, the 2D-3D registration is introduced. The role of 2D-3D registration is to enhance the quality of the surgical procedure in terms of time and accuracy, and would greatly reduce the need for repeated surgeries; thus, saving the patients time, expense, and trauma. vi TABLE OF CONTENTS DEDICATION ................................................................................................................... iii ACKNOWLEDGEMENTS ............................................................................................... iv ABSTRACT ........................................................................................................................ v LIST OF TABLES ............................................................................................................. xi LIST OF FIGURES ......................................................................................................... xiii CHAPTER 1 ....................................................................................................................... 1 INTRODUCTION .......................................................................................................... 1 1.1 Introduction .............................................................................................................. 1 1.2 Motivation behind This Work .................................................................................. 2 1.2.1 Shape Registration and Vertebral Body segmentation .......................................... 2 1.2.2 Image Registration and Ankle Fusion.................................................................... 4 1.3 Contributions of This Dissertation ........................................................................... 6 1.4 Document Structure ................................................................................................. 8 CHAPTER 2 ..................................................................................................................... 11 FUNDAMENTALS OF LEVEL SETS METHODS ................................................... 11 2.1 Definitions .......................................................................................................... 13 2.1.1 Simple Closed Curve ....................................................................................... 13 2.2.2 Curvature.......................................................................................................... 13 2.2.3 Distance Transform .......................................................................................... 14 vii 2.2 Idea of Curve Evolution ..................................................................................... 15 2.3 Representation of an Evolving Contour/Interface .............................................. 16 2.3.1 Parameterized representation (Snakes) ............................................................ 16 2.3.2 Level sets representation (Geometric active contour) ..................................... 18 2.4 Mathematical Formulations................................................................................ 20 2.5 Solution of Level Set Equation ............................................................................... 22 2.6 The Effects of Curvature and Viscosity Solutions .................................................. 22 2.7 Motion under Curvature (Curvature Flow) ............................................................. 24 2.8 A level Set Formulation for Willmore Flow ........................................................... 25 CHAPTER 3 ....................................................................................................................
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