A Method to Differentiate Mild Cognitive Impairment and Alzheimer in MR Images using Eigen Value Descriptors

Abstract

Automated analysis and differentiation of mild cognitive impairment and Alzheimer's condition using MR images is clinically significant in dementic disorder. Alzheimer's Disease (AD) is a fatal and common form of dementia that progressively affects the patients. Shape descriptors could better differentiate the morphological alterations of brain structures and aid in the development of prospective disease modifying therapies. Ventricle enlargement is considered as a significant biomarker in the AD diagnosis. In this work, a method has been proposed to differentiate MCI from the healthy normal and AD subjects using Laplace-Beltrami (LB) eigen value shape descriptors. Prior to this, Reaction Diffusion (RD) level set is used to segment the ventricles in MR images and the results are validated against the Ground Truth (GT). LB eigen values are infinite series of spectrum that describes the intrinsic geometry of objects. Most significant LB shape descriptors are identified and their performance is analysed using linear Support Vector Machine (SVM) classifier. Results show that, the RD level set is able to segment the ventricles. The segmented ventricles are found to have high correlation with GT. The eigen values in the LB spectrum could show distinction in the feature space better than the geometric features. High accuracy is observed in the classification results of linear SVM. The proposed automated system is able to distinctly separate the MCI from normal and AD subjects. Thus this pipeline of work seems to be clinically significant in the automated analysis of dementic subjects.

The Comprehensive Assessment of Neurodegeneration and Dementia: Canadian Cohort Study

“…CDIP will also be used in a growing number of other Canadian brain study cohorts, including ONDRI, CIMA-Q, and the Canadian Alliance for Healthy Hearts and Minds. 44 By using exactly the same sequences in these different studies, the potential to combine and compare across them becomes possible.…”

Differentiation of Alzheimer Conditions in MR Brain Images Using a Single Inception Module Network

“…It is estimated that by 2050, 152 million populations worldwide will suffer from AD [1]. Due to the increasing prevalence, accurate diagnosis of the prodromal stage of AD, Mild Cognitive Impairment (MCI), is crucial for delaying the progression of the disease [2].…”

“…Based on sMRI estimates, several Computer-Aided Decision support (CAD) systems have been developed for the early prediction of AD [2][3]. Some of the CAD approaches include k-nearest neighbor [3] and support vector machine [2]. These methods employ handcrafted features which may not be suitable with subsequent classifiers, thus leading to reduction in the performance of the system.…”

Systematic and Comprehensive Automated Ventricle Segmentation on Ventricle Images of the Elderly Patients: A Retrospective Study

“…The volume of the ventricle has always been closely related to degenerative brain diseases and traumatic brain injury. Researchers have also described that enlargement of the ventricles is an important characteristic of medical conditions such as schizophrenia, Parkinson's disease, Alzheimer's disease, hydrocephalus, and trauma to the brain (Silbert et al, 2003;Thompson et al, 2004;Chou et al, 2009;Liu et al, 2010;Cavedo et al, 2012;Khan et al, 2012;Anandh et al, 2016;Del et al, 2016;Owen et al, 2018;Kocaman et al, 2019;Lundervold et al, 2019). In some disease diagnosis guidelines, EI > 0.3 is often defined as ventricular enlargement (Relkin et al, 2005;Mori et al, 2012).…”