Image Classification of Magnetic Resonance Imaging in Autism Spectrum Disorder
Autor: | Chin-Hsuan HUANG, 黃沁萱 |
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Rok vydání: | 2019 |
Druh dokumentu: | 學位論文 ; thesis |
Popis: | 107 Early detection and treatments for Autism Spectrum Disorder (ASD) are beneficial in improving the life quality of a patient and his/her family. A recent survey studied deep learning techniques which have been developed over the past decade in detecting various brain diseases from MRIs. Some works which used rs-fMRI for diagnosing ASD were able to obtain diagnostics with an accuracy between 65.56% and 70%. In this research, instead of fMRI, a CNN-based model was proposed to identify reliable ASD-related biomarkers from sMRI. The sMRI images were spatially registered into the MNI stereotaxic space using FMRIB Software Library. In the work a 67.14% diagnosis accuracy and 73% AUC ROC were achieved, which were comparable to other studies using fMRI. |
Databáze: | Networked Digital Library of Theses & Dissertations |
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