Department of Computer Science and Engineering
University of Washington

Improving Melanoma Pathology Accuracy through Computer Vision Techniques
The IMPACT Study

This research is supported by the National Cancer Institute grant R01 CA200690, PI: Dr. Joann Elmore.

In this project, novel computational techniques are being used to analyze digitized slides for the purpose of assisting in the pathologic diagnosis of melanoma and related skin lesions. These techniques include the detection of both cellular-level and architectural features for use in feature-based classification, and exploration of deep neural networks that operate on raw pixel data for the difficult task of mitosis detection. In addition, a machine learning approach will be applied to the digitized slides to determine the histopathological characteristics associated with human diagnostic errors.

People:

Joann Elmore
Linda Shapiro
Shima Nofallah
Meredith Wu
Beibin Li
Sachin Mehta
Ximing Lu
Donald Weaver
Oliver Chang
Caitlin May
Stevan Knezevitch

Recent Foundational Model Work


Publications:

Presentations: