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Mount Sinai Hospital
Joseph & Wolf Lebovic Health Complex
600 University Avenue
Toronto, Ontario
M5G 1X5
Tel.: 416-586-4800
► Web of Science Researcher ID
Q-1315-2017
Dr. Masoom Abbas Haider
SENIOR CLINICIAN SCIENTIST
Dr. Masoom Haider is Director of the Sinai Health Research MRI and Head of the Radiomics and Machine Learning Lab at Mount Sinai Hospital. He is a Staff Radiologist, in the Joint Dept of Medical Imaging at Mount Sinai Hospital and Princess Margaret Hospital, Senior Clinician Scientist, LTRI and Professor, Department of Medical Imaging, University of Toronto as well as an Ontario Institute of Cancer Research Clinician Scientist. He was previously Chief, Medical Imaging, Sunnybrook Health Sciences Centre and Head of Abdominal MRI.
He received his MD from the University of Ottawa and undertook additional training at the University of Toronto and the Cleveland Clinic Foundation.
Dr. Haider’s research focuses on prostate cancer localization with MRI using multiparametric approaches; radiological pathologic correlation in prostate cancer, GU malignancies and other abdominal and pelvic malignancies; and feature analysis of tumors for imaging biomarker validation (radiomics) and therapy response assessment.
He is also interested in functional assessment of tumors using MRI and CT, pancreatic and hepatobiliary cancer assessment with MRI and computer-aided diagnosis.
Dr. Haider holds three patents on technologies related to medical imaging as well as intellectual property related to medical imaging teaching. He has published more than 200 publications in peer-reviewed journals.
At a Glance
Head of the Radiomics and Machine Learning Lab at Mount Sinai Hospital
Staff Radiologist, Joint Dept of Medical Imaging, Mount Sinai Hospital and Princess Margaret Hospital, Senior Clinician Scientist, LTRI and Professor, Department of Medical Imaging, University of Toronto
Expert in oncologic imaging with a research focus in abdominal and pelvic MRI and therapeutic response assessment using Machine Learning and quantitative imaging (radiomics) of cancer
Major Research Activities
Currently our team is using machine learning and artificial intelligence methods combined with quantitative imaging biomarkers derived from radiomics to develop predictive and prognostic signatures from MRI and CT in prostate and pancreatic cancer. In prostate cancer, automated segmentation of the prostate and cancer sites on multiparametric MRI is being developed to aid in treatment planning and reproducible interpretation for precision medicine. In pancreatic cancer, a better understanding of radiologic pathologic correlates for non invasive assessment of the tumor microenvironment are being studied. A computational image analysis pipeline that incorporates the expertise of radiologists, pathologists and oncologists around medical imaging forms the core of the lab.
