Evaluation of Deep Learning-Based Segmentation of Nuclei from Fluorescence Microscopy Images
Overview: Nucleus segmentation from fluorescence microscopy images of cells stained with a DNA dye or other nuclear marker is a critical first step in many automated image processing pipelines. In this one-hour presentation, Dr. George Zaki (FNL/CBIIT) offers a practical approach for evaluating deep learning methods for nucleus segmentation – using state of the art neural networks.
Date: Tuesday, March 3, 2020
Time: 1:00-2:00 p.m.
Location: NCI Shady Grove, 3E032-034
Questions? Contact the NCI Data Science Learning Exchange