Abstract #2727

Generalized AI for Organ Invariant Tissue Segmentation and Characterization of Multiparametric MRI: Preliminary Results

Vishwa Sanjay Parekh¹, Katarzyna J Macura^2,3, and Michael A Jacobs^2,3

¹Department of Computer Science, Johns Hopkins University, Baltimore, MD, United States, ²The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ³Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States

Artificial intelligence(AI) and deep learning techniques are increasingly being used in radiological applications. The true potential of deep learning in MRI applications can only be achieved by developing an AI that can learn the underlying MRI physics rather than a task that is specific to an organ or a particular tissue pathology. To that end, we developed and tested a multiparametric deep learning model capable of tissue segmentation and characterization in both breast cancer and stroke.

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