Year: 2022

StyleGAN2-based Out-of-Distribution Detection for Medical Imaging

extended abstract

Volunteering through the TRAIN initiative to teach machine learning to 40 high school students across the United States.

Woodland, M. et al. (2022). Evaluating the Performance of StyleGAN2-ADA on Medical Images. In: Zhao, C., Svoboda, D., Wolterink, J.M., Escobar, M. (eds) Simulation and Synthesis in Medical Imaging. SASHIMI 2022. Lecture Notes in Computer Science, vol 13570. Springer, Cham. https://doi.org/10.1007/978-3-031-16980-9_14

Paper entitled “Evaluating the performance of StyleGAN2-ADA on Medical Images” to be published in the conference proceedings of the SASHIMI (Simulation and Synthesis in Medical Imaging) workshop as part of the 2022 MICCAI conference. Workshop will be held on September 18th in Singapore.

Became a member of The Coding School‘s Young Professional Advisory Board. I will specifically be giving guidance on the AI curriculum development for the TRAIN grant.

Poster entitled “StyleGAN2-based Out-of-Distribution Detection in Computed Tomography” will be presented at the Practical Big Data Workshop (Ann Arbor, Michigan).

Abstract entitled “Comparing Transfer Learning, Data Augmentation, and Data Expansion in the Improvement of Medical Image Generation” will be presented in the 2022 AAPM annual meeting during the “AI/ML Autoplanning, Autosegmentation, and Image Processing 1” session. This session is from 1-2pm in Ballroom B.

Teaching CSE 450: Machine Learning & Data Mining

Abstract entitled “Improving the Generation of Synthetic Medical Images using Data Augmentation and Transfer Learning” chosen for a poster presentation at the Young Investigator’s Symposium at SWAAPM 2022. The top 20 abstracts were chosen for the session.

In addition, my presentation entitled “Houston, Our AI Models Have a Problem!” was selected for the MedPhys Slam competition.