AI in 3D Medical Images: Concepts, Milestones, and Opportunities

Speaker: Yangming Ou, PhD, at Boston Children's Hospital

Date: July 17, 2020 at 09:30AM - 10:30AM

Dr. Yangming Ou briefly reviewed some major concepts and milestones of AI in medical images. The focus of Dr. Ou’s talk was on 3D medical images, for AI’s application in disease diagnosis, outcome prediction, early screening, neuroscience, and others. Dr. Ou then discussed some major challenges and potential opportunities, including further improving accuracy in detecting small diffuse lesions, and facilitating AI in small sample sizes.

Dr. Yangming Ou's research focuses on improving healthcare by medical image analysis, machine learning and imaging informatics. One pillar of Dr. Ou's lab is in developing MRI analysis and MRI machine learning algorithms. This includes algorithms for spatiotemporal MRI analysis, multi-modal MRI integration, quantification of normal brain development, detection of abnormalities, prediction of outcomes, treatment evaluation, and disease subtyping. Another pillar of Dr. Ou's lab is in applying advanced imaging informatics for clinical studies. The topics span mild, moderate and severe brain abnormalities. Mild conditions studied in the lab includes nutrition insufficiency and kids with in-utero exposure to opioid. Moderate conditions include hypoxic ischemic injury, rare diseases such as Sturge-Weber Syndrom, early screening of psychosis, dyslexia, etc. Severe diesease include pediatric brain tumor and how to improve neurocognitive outcomes in survivors. Dr. Ou holds a PhD degree in Medical Image Analysis and an MS degree in Applied Mathematics, both from the University of Pennsylvania. His BS degree was in Electrical Engineering (Biomedical Engineering Division) from Tsinghua University. His research interest lies in the intersection of big data, machine learning, data science, imaging informatics, and healthcare.

Publications

Hopper RK, Abman SH, Elia EG, Avitabile CM, Yung D, Mullen MP, Austin ED, Bates A, Handler SS, Feinstein JA, Ivy DD, Kinsella JP, Mandl KD, Raj JU, Sleeper LA, . Pulmonary Hypertension in Children with Down Syndrome: Results from the Pediatric Pulmonary Hypertension Network Registry. The Journal of pediatrics 2022.

Wang X, Zhang HG, Xiong X, Hong C, Weber GM, Brat GA, Bonzel CL, Luo Y, Duan R, Palmer NP, Hutch MR, Gutiérrez-Sacristán A, Bellazzi R, Chiovato L, Cho K, Dagliati A, Estiri H, García-Barrio N, Griffier R, Hanauer DA, Ho YL, Holmes JH, Keller MS, Klann MEng JG, L'Yi S, Lozano-Zahonero S, Maidlow SE, Makoudjou A, Malovini A, Moal B, Moore JH, Morris M, Mowery DL, Murphy SN, Neuraz A, Yuan Ngiam K, Omenn GS, Patel LP, Pedrera-Jiménez M, Prunotto A, Jebathilagam Samayamuthu M, Sanz Vidorreta FJ, Schriver ER, Schubert P, Serrano-Balazote P, South AM, Tan ALM, Tan BWL, Tibollo V, Tippmann P, Visweswaran S, Xia Z, Yuan W, Zöller D, Kohane IS, Avillach P, Guo Z, Cai T, . SurvMaximin: Robust federated approach to transporting survival risk prediction models. Journal of biomedical informatics 2022.

Torous J, Stern AD, Bourgeois FT. Regulatory considerations to keep pace with innovation in digital health products. NPJ digital medicine 2022.

Levy S, Wisk LE, Minegishi M, Ertman B, Lunstead J, Brogna M, Weitzman ER. Association of Screening and Brief Intervention With Substance Use in Massachusetts Middle and High Schools. JAMA network open 2022.

Nielsen M, Presti M, Sztupinszki Z, Jensen AWP, Draghi A, Chamberlain CA, Schina A, Yde CW, Wojcik J, Szallasi Z, Crowther MD, Svane IM, Donia M. Co-existing alterations of MHC class I antigen presentation and IFNγ signaling mediate acquired resistance of melanoma to post-PD-1 immunotherapy. Cancer immunology research 2022.
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