MIMRTL Team Presents Work at SIIM 2023

The MIMRTL team had several presentations at the Society for Imaging Informatics (SIIM) Annual Meeting in that occurred June 14th-16th in Austin, Texas. The team presented work on differential privacy in medical imaging, use of ontology mapping to aid in machine learning classification of medical images, and automated ways to detect body regions in medical images. Congrats Team, especially lead authors Xue Li, Sabeeka Khan, and Michael Fei for their contributions!

A bibliography of the MIMRTL team’s presented work at SIIM is here:

Fei M, Estakhraji S, McMillan A. (2023). Deeper Models for Self-Supervised Body Part Regression. Society for Imaging Informatics in Medicine (SIIM) Annual Meeting. Austin, Texas. Poster Presentation

Kahn S, Zhang J, Joshi T, Uyanik M, Loh P, Jog V, Bruce R, Garrett J, McMillan A. (2023). Training Private Deep Learning Models for Medical Image Analysis. Society for Imaging Informatics in Medicine (SIIM) Annual Meeting. Austin, Texas. Oral Presentation.

Li X, Sampat M, Pannetier N, McMillan A, Garrett J, Bruce R. (2023). Leveraging the LOINC/RSNA Radiology Playbook for Metadata Expansion, QA, and Generalizability in ML Ops. Society for Imaging Informatics in Medicine (SIIM) Annual Meeting. Austin, Texas. Oral Presentation.

Li X, Pannetier N, Sampat M, Richardson T, Bruce R, Garrett J, McMillan A. (2023). Automated Body Region Identification for Radiography Studies. Society for Imaging Informatics in Medicine (SIIM) Annual Meeting. Austin, Texas. Oral Presentation.

Martin-Carreras T, Premkumar H, McMillan A, Tang J. (2023) Machine Learning (ML) Distinguish Lipomas From Atypical Lipomatous Tumor/Well-Differentiated Liposarcomas Using Radiomic Features Extracted From MRI. Society for Imaging Informatics in Medicine (SIIM) Annual Meeting. Austin, Texas. Oral Presentation

The SIIM 2023 abstract book is available here.