Machine Learning and Artificial Intelligence

Breakfast Workshop B

Date/Time: Friday, May 1, 2020 - 7:30 AM to 8:30 AM
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Machine Learning and Artificial Intelligence

In the last few years we saw tremendous advances in computer vision and deep learning for improving the usage of non-invasive imaging as diagnostic and prognostic tools of degenerative joint disease. We are able today to develop deep learning convolutional neural networks for musculoskeletal tissue segmentation and abnormality detection; severity staging and functional classification ranging on different imaging modalities from X-ray, CT and MRI. We can build multi-modal integrated frameworks by using biochemical and morphological features extracted from MR imaging, demographics, family history and genetic data simultaneously, to predict future outcomes and disease trajectories. For a clinically feasible translation of the developed models and to achieve the unmet challenge of a comprehensive, quantitively, automatic and data-driven imaging evaluation of the musculoskeletal system, efficient simultaneous data acquisition and processing are necessary. In this workshop some basics on the usage of deep learning to study OA will be covered by reviewing the current state of the art on diagnostic and prognostic application of deep learning on OA. We will also cover some applications of deep learning to MRI acceleration and automated processing.