Presentation: UND, NDSU, & ND-ACES bio and biomedical computation networking seminar
November 20, 2024, Alerus Center, Grand Forks, North Dakota
Machine learning for ND-ACES biomedical images: successes and challenges
Yen Lee
Loh
Faculty Member
University of North Dakota
Co-authors: Aliakbar Sepehri, Dr., UND; Ian Bergerson, Mr., UND
Session
Presentation Session 2
My group has been using machine learning techniques (convolutional neural networks) to perform image segmentation and analysis on microscope images from the Combs group (UND) and the Wilkinson group (NDSU). The datasets include time series images of MDA-MB-231 and PC3 cell cultures in 2D at various densities, as well as co-cultures of MDA-MB-231 breast cancer cells and pre-treated macrophages. I will discuss what we were able to achieve and the difficulties we faced.
The ND-ACES NSF Track-1 cooperative agreement is a federal-state partnership to manage a comprehensive research development plan. ND EPSCoR manages the Track-1 award. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Current funding is provided by the State of North Dakota and NSF EPSCoR Research Infrastructure Improvement Program Track-1 (RII Track-1) Cooperative Agreement Award OIA #1946202.