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A Comprehensive Survey on Tools for Effective Alzheimer's Disease

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A Comprehensive Survey on Tools for Effective Alzheimer's Disease Neuroscience International Literature Reviews A Comprehensive Survey on Tools for Effective Alzheimer’s Disease Detection Vinutha, N., G.U. Vasanthakumar, P. Deepa Shenoy and K.R. Venugopal Computer Science and Engineering, University Visvesvaraya College of Engineering, India Article history Abstract: Neuroimaging is considered as a valuable technique to study the Received: 16-06-2017 structure and function of the human brain. Rapid advancement in medical Revised: 16-08-2017 imaging technologies has contributed significantly towards the Accepted: 22-09-2017 development of neuroimaging tools. These tools focus on extracting and enhancing the relevant information from brain images, which facilitates Corresponding Author: Vinutha, N. neuroimaging experts to make better and quick decision for diagnosing Computer Science and enormous number of patients without requiring manual interventions. This Engineering, University paper describes the general outline of such tools including image file Visvesvaraya College of formats, ability to handle data from multiple modalities, supported Engineering, India platforms, implemented language, advantages and disadvantages. This brief review of tools gives a clear outlook for researchers to utilize existing Email: [email protected] techniques to handle the image data obtained from different modalities and focus further for improving and developing advanced tools. Keywords: Alzheimer’s Disease, Computer Aided Diagnosis, Imaging, Morphometry, Neuroimaging Tools Introduction challenging and requires further investigations through popular neuroimaging techniques (Joshi et al., 2010). Alzheimer’s Disease (AD) is one of the most Neuroimaging (Poldrack et al., 2008) or brain common neurodegenerative diseases affecting older imaging is an important tool for understanding the adults in their mid-60s (Joshi et al., 2010). Degeneration anatomy and function of the human brain. Parameters of the nervous system is mainly caused due to the such as tissue contraction, volume reduction and deposition of amyloid plaques and neurofibrillary expansion, variation of shape, average intensity, tangles (Hardy and Selkoe, 2002). Symptoms generally metabolism rate and cortical thickness are of great include memory loss, impairment in thinking, poor interest to determine AD. These parameters can be obtained using a range of different techniques such as judgement and difficulty in recognising people. Since Magnetic Resonance Imaging (MRI), Fluorodeoxyglucose the number of patients with AD is expected to increase Positron Emission Tomography (FDG-PET), Diffusion in near future, the National Institute of Aging has been Tensor Imaging (DTI), Functional Magnetic Resonance focusing towards the development of effective Imaging (fMRI), Computed Tomography (CT), Single techniques to diagnose AD. Photon Emission Computed Tomography (SPECT) and The transition to AD from normal aging is gradual; Cerebrospinal Fluid (CSF) Biomarkers. thus, many researchers have put attention towards the Among these techniques, MRI is reliable and non- early detection of AD. The early stage of AD is invasive for producing high resolution images. It does represented by the term, Mild Cognitive Impairment not cause adverse sideeffects in patients; thus, it is (MCI) (Petersen, 2011). Two different subtypes of MCI considered as a significant technique to fetch both are Amnestic Mild Cognitive Impairment (aMCI) and structural and functional information of the brain to Non amnestic Mild Cognitive Impairment (naMCI). study further. MRI is also preferred in predicting the aMCI patients have significantly impaired memory, but shift from MCI to AD by either considering the whole their cognitive functions remain effective. On the other brain or medial temporal lobe volume. However, MRI hand, in case of naMCI, one or more cognitive skills are being a single modality technique does not provide impaired but memory problem remains unaffected. Patients comprehensive information. Hence, multimodal data with MCI have increased risks of eventually developing analyzed by radiologists or neurologists using AD. Thus, identification of AD at the early stage is neuroimaging tools are preferred as sources of valuable © 2018 Vinutha, N., G.U. Vasanthakumar, P. Deepa Shenoy and K.R. Venugopal. This open access article is distributed under a Creative Commons Attribution (CC-BY) 3.0 license. Vinutha, N. et al. / Neuroscience International 2018, Volume 9: 1.10 DOI: 10.3844/amjnsp.2018.1.10 information for assisting the diagnosis and prognosis of from the dataset into a suitable format required for AD or MCI at early stages. preprocessing. MRIcron, SPM and Free Surfer are few of the tools which are used for data conversion. Motivation Sequences of preprocessing steps are followed Experts in the field of Neurology or Radiology are according to the requirement of postprocessing required to investigate problems associated with the operations desired for a particular application. It includes complex brain structure. To overcome this manual and the removal of non-brain tissues (Zhuang et al., 2006) time consuming process, there is advancement towards from T1 and T2 weighted Magnetic Resonance (MR) the development of neuroimaging tools. Tools developed images. A skull-stripped subject image is spatially in the past are standalone techniques, which has aligned to a standard template through the process of motivated researchers and developers to design an open Spatial Normalisation (Friston et al., 1995), which helps source tool with Graphical User Interface (GUI) to overcome the problem of brain shape variability providing compatibility to multiple operating systems. Based on the application and requirement, tools across different subjects. AC-PC (Anterior Commissure- contributed by developers are enormous. Few tools Posterior Commissure) positioning aligns coordinates of provide easy and convenient way of installation and the brain by their origin and axes, which is adopted as a usage, but some of them have complicated procedures convenient standard by the neuroimaging Community. requiring high memory for processing three/four Coordinate convertor converts the coordinate from display dimensional images to get desired results. to Talairach and Montreal Neurological Institute (MNI) space. N3 inhomogeneity correction (Vovk et al., 2007) Contribution removes the intensity inhomogeneity across space caused In the present review, the ability of various during the acquisition of MR images from the scanner. neuroimaging tools to handle image data from different Smoothening removes Gaussian Noise and Histogram types of modalities, languages in which they are Equalisation enhances images for redistributing the gray implemented, as well as various supporting value to acquire an uniform distribution. functionalities are discussed. After preprocessing, the image is subjected to tissue Organisation segmentation (Tanabe et al., 1997; Vibha et al., 2007) to divide it into the gray matter, white matter and The paper is organized as follows: A brief overview cerebrospinal fluid. Due to the neuronal loss caused by of Alzheimer’s Disease is provided in Section I. Related the deposition of amyloid plaques and neurofibrillary research are presented in Section II. Morphometry tangles, cortical gray matter reduction occurs to a greater techniques are described in Section III. Tools in extent compared to white matter and cerebrospinal fluid; neuroimaging are explained in Section IV. A brief hence, the gray matter is considered for further analysis. discussion about the tools are presented in Section V. A Segmentation (Kumar et al., 2009) is followed by comprehensive conclusion is provided in Section VI. registration to establish the correspondence between a set of images using transformation models and assess by Literature Survey considering similarity measures. Many of open source tools have wide range of steps Image registration (Gholipour et al., 2007) is the beginning with the preprocessing operation and ending most crucial step required in the medical imaging, which with the analysis, which are essential to classify patients is described as the process of geometric alignment of the with neurodegenerative disorders. These steps are subject image to the template to bring it in discussed in further paragraphs. correspondence. It involves the extraction of information In the study of neurodegenerative disorders from the feature space and transformation of the image particularly Alzheimer’s Disease (AD), image data are required for matching. Affine, polynomial and elastic provided by the standard dataset like Alzheimer’s transformations are different types of spatial Disease Neuroimaging Initiative (ADNI), Open Access transformation techniques available to transform the Series of Imaging Studies (OASIS) and The Minimal image. Transformation technique is the fundamental Interval Resonance Imaging in Alzheimer’s Disease characteristic in the process of registration to overlay (MIRIAD), which are available in DICOM (Digital Imaging and Communications in Medicine), NIFTI images on each other. The amount of transformation is (Neuroimaging Informatics Technology Initiative), measured by the chosen similarity metric. Images MINC and Analyze format. To suit the compatibility of considered during registration are taken from the same data required for processing, the initial step is data modality acquired during different time periods, which conversion. It is required for converting images obtained aid in determining
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