Isocitrate Dehydrogenase 1 Mutation Status of Low-Grade Gliomas Prediction from Radiomics Biomarkers of Conventional MRI scans
In 2016, the world health organization recommended using genotypic information such as isocitrate dehydrogenase (IDH) mutation status for grading and treatment planning of the central nervous system cancers such as low-grade gliomas. This presentation proposes a machine learning technique to predict Isocitrate dehydrogenase 1 (IDH 1) gene mutation status from T1, T1-Gd, T2, and T2-fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) sequences.
Biography
Mojtaba Safari is a Ph.D. student at Medical Physics program at the Département de physique, de génie physique et d'optique in the Université Laval. Mojtaba is doing Ph.D. under the supervision of Louis Archambault.
Mojtaba is interested in MRI physics and quantitative MRI sequences. He is also passionate about machine learning (ML) applications in medical imaging. He has done some projects on quantitative MRI sequences radiomics biomarkers for predicting brain tumor type and grade.
