CLASSIFICATION TECHNIQUES FOR AUTISTIC VS. TYPICALLY DEVELOPING BRAIN USING MRI DATA

This publication is included in the Autistic Autism Scholarship Project. one author of this publication is identified as autistic in the project.

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Fahmi, R., El-baz, A., Abd El Munim, H., Farag, A., & Casanova, M. (2007). CLASSIFICATION TECHNIQUES FOR AUTISTIC VS. TYPICALLY DEVELOPING BRAIN USING MRI DATA. 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 1 2, 1348-1351. https://doi.org/10.1109/isbi.2007.357110

Publication date: 1 Jan 2007 Added to AutiHub: 14 Sep 2026 Type: Other Article language: English
Publisher source (DOI) OpenAlex source

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Authors

Publication authors
5
Publication authors identified as autistic
1 / 5 (20.0%)
  1. Rachid Fahmi
  2. Ayman El-baz
  3. Hossam Abd El Munim
  4. Aly Farag
  5. Manuel Casanova *

Abstract

Autism is a neurodevelopmental disorder that disrupts social and cognitive functions. Various autism studies revealed abnormalities in several brain regions. There is an increasing agreement from structural imaging studies on the abnormal anatomy of the white matter (WM) in autistic brains. In addition, the deficits in the size of the corpus callosum (CC) and its sub-regions in patients with autism relative to controls are well established. This paper presents two novel classification techniques of autism based on structural MRI. Our analysis is based on shape descriptions and geometric models. We compute the 3D distance map to describe the shape of the WM and use it as a statistical feature to discriminate between the two groups. We also use our recently proposed non-rigid registration technique to devise another classification approach by statistically analyzing and comparing the deformation fields generated from registering CC's onto each others. The accuracy of our techniques was tested on postmortem and on in vivo brain MR data. The results are very promising and show that, contrary to traditional methods, the proposed techniques are less sensitive to age and volume effects

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 14 Sep 2026 14:22.

Cited references
19
With a DOI
16
Without a DOI, from raw bibliography text
3
0 / 19 (0.0%) cited references include at least one author identified as autistic.
References with data to complete
1 / 19 (5.3%)
References with detected author names
18 / 19 (94.7%)
Without detected author names
1
Without a structured title
1
Without a stable identifier
2
References with raw author names still to review
0
References with external metadata lookup issues
1
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
89
From DOI or external metadata
89
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
0
15 / 89 (16.9%) names are linked to an author already present in AutiHub. 74 / 89 (83.1%) names are not yet linked.
Names linked to a person identified as autistic
0 / 89 (0.0%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 0 / 15 (0.0%). Distinct people identified as autistic: 0 / 83 (0.0%).
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    Type: Other
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