MedAI

Title: Towards Robust Radiomics and Radiogenomics Predictive Models for Brain Tumor Characterization
Speaker: Hassan Mohy-ud-Din
Abstract:
In the context of brain tumor characterization, we focused on two key questions which, to the best of our knowledge, have not been explored so far: (a) stability of radiomics features to variability in multiregional segmentation masks obtained with fully-automatic deep segmentation methods and (b) subsequent impact on predictive performance on downstream prediction tasks. The hypothesis is that highly stable and discriminatory radiomics features lead to generalizable radio(geno)mics models for brain tumor characterization.
Speaker Bio:
Dr. Hassan Mohy-ud-Din is the Director of Algorithms in Theory and Practice Lab and an Assistant Professor of Electrical Engineering, Syed Babar Ali School of Science and Engineering, LUMS. He completed his PhD and MSE in Electrical and Computer Engineering and MA in Applied Mathematics and Statistics from Johns Hopkins University (2009 - 2015). From 2015 - 2017 he was a postdoctoral associate in the Department of Radiology and Biomedical Imaging at the Yale School of Medicine. From 2017 - 2018 he was a Clinical Research Scientist at Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan. His research is at the intersection of applied mathematics and clinical imaging - exploiting tools in machine learning, optimization, statistics, and information theory to develop novel algorithms for clinical and translational imaging. He has done extensive research in multimodality imaging including PET/CT, SPECT/CT, PET/MR, Low-dose CT, and multiparametric MRI and developed computational pipelines for brain imaging, cardiac imaging, and abdominal imaging. His work on dynamic cardiac PET imaging won the 2014 SNMMI Bradley-Alavi fellowship and the 2014 SIAM student award. He is also a recipient of the 2019 Charles Wallace Fellowship from the British Council, Pakistan. He carries a university teaching experience of over fifteen years (including five years at Johns Hopkins University).
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