Autism Diagnostics by 3D Shape Analysis of the Corpus Callosum

Autism Diagnostics by 3D Shape Analysis of the Corpus Callosum

Ahmed Elnakib (University of Louisville, USA), Manuel F. Casanova (University of Louisville, USA), Georgy Gimel’farb (University of Auckland, New Zealand) and Ayman El-Baz (University of Louisville, USA)
DOI: 10.4018/978-1-4666-0059-1.ch015
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Abstract

The importance of accurate diagnostics of autism that severely affects personal behavior and communication skills cannot be overstated. Neuropathological studies have revealed an abnormal anatomy of the Corpus Callosum (CC) in autistic brains. This chapter proposes a new approach to quantitative analyses of three-dimensional (3D) Magnetic Resonance Images (MRI) of the brain that ensures a more accurate quantification of the anatomical differences between the CC of autistic and normal subjects. It consists of three main processing steps: (1) segmenting the CC from a given 3D MRI using the learned CC shape and visual appearance; (2) extracting a centerline of the CC; and (3) cylindrical mapping of the CC surface for its comparative analysis. The authors’ experiments revealed significant differences (at the 95% confidence level) between 17 normal and 17 autistic subjects in four anatomical divisions (i.e. splenium, rostrum, genu, and body of their CCs). Moreover, the initial classification results suggest that the proposed centerline-based shape analysis of the CC is a promising supplement to the current techniques for diagnosing autism.
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Background

Neuropathological and neuroimaging studies have revealed a great deal concerning the pathogenesis of autism. An overview of these studies as well as the proposed approach for analyzing MRI images of autistic and control subjects is illustrated below.

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