Deep Learning Methods for Computed Tomography and Magnetic Resonance Images
Medical imaging, (e.g., computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), mammography, ultrasound, X-ray) has advanced at a rapid speed over last decades. Currently, the medical image interpretation is mostly performed by human experts, which is a tedious task and subject to high inter-operator variability. Deep learning is providing exciting solutions for automated medical image analysis problems. Recent advances in deep learning have helped to identify, classify, and quantify patterns in medical images. In this seminar, the principles and methods of deep learning concepts, particularly convolutional neural network (CNN) will be introduced. I will describe several interesting applications of deep learning for medical image analysis, including my recent works on segmenting myocardial scar (injured) tissue in the heart, prostate tumor detection, and kidney lesion localization in 3D MRI and CT images.
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- Ottawa, Ontario
- Canada
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Dr. Fatemeh Zabihollahy