A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data
| dc.contributor.author | Ghazal, Mohammed | |
| dc.contributor.author | Dekhil, Omar | |
| dc.contributor.author | Ali, Mohamed | |
| dc.contributor.author | ETAL.. | |
| dc.date.accessioned | 2021-12-21T12:28:10Z | |
| dc.date.accessioned | 2023-08-19T08:56:40Z | |
| dc.date.available | 2021-12-21T12:28:10Z | |
| dc.date.available | 2023-08-19T08:56:40Z | |
| dc.date.issued | 2019-07 | |
| dc.description | Autism spectrum disorder (ASD) is a neuro-developmental disorder that has three main associated characteristics (1): i) social functioning disorders, ii) communication impairments, and iii) restricted and repetitive behaviors (RRBs). In many previous research projects, correlation was reported between autism and both anatomical abnormalities and functional activation abnormalities. For studying anatomical abnormalities, the most commonly used imaging modality is structural MRI (sMRI) (2), while functional MRI (fMRI) is the most commonly used modality for studying brain activation (3). | en_US |
| dc.description.abstract | Autism spectrum disorder is a neuro-developmental disorder that affects the social abilities of the patients. Yet, the gold standard of autism diagnosis is the autism diagnostic observation schedule (ADOS). In this study, we are implementing a computer-aided diagnosis system that utilizes structural MRI (sMRI) and resting-state functional MRI (fMRI) to demonstrate that both anatomical abnormalities and functional connectivity abnormalities have high prediction ability of autism. The proposed system studies how the anatomical and functional connectivity metrics provide an overall diagnosis of whether the subject is autistic or not and are correlated with ADOS scores. The system provides a personalized report per subject to show what areas are more affected by autism-related impairment. Our system achieved accuracies of 75% when using fMRI data only, 79% when using sMRI data only, and 81% when fusing both together. Such a system achieves an important next step towards delineating the neurocircuits responsible for the autism diagnosis and hence may provide better options for physicians in devising personalized treatment plans. | en_US |
| dc.identifier.citation | Dekhil, O., Ali, M., El-Nakieb, Y., Shalaby, A., Soliman, A., Switala, A., ... & Barnes, G. (2021). A personalized autism diagnosis CAD system using a fusion of structural MRI and resting-state functional MRI data. Frontiers in psychiatry, 10, 392. | en_US |
| dc.identifier.doi | https://doi.org/10.3389/fpsyt.2019.00392 | |
| dc.identifier.uri | https://edms.wexl.in/handle/1/1855 | |
| dc.language.iso | en | en_US |
| dc.publisher | Frontiers in Psychiatry | en_US |
| dc.subject | Autism | en_US |
| dc.subject | Spectrum disorder | en_US |
| dc.subject | Functional MRI data | en_US |
| dc.title | A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data | en_US |
| dc.title.alternative | Journal article | en_US |
| dc.type | Article | en_US |
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