Regions-of-Interest Detection in big histopathological images

Principal Investigator

Name
Li Sulimowicz

Degrees
PhD

Institution
University of Texas at Arlington

Position Title
Phd student in Computer Science

Email
li.yin@mavs.uta.edu

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-237

Initial CDAS Request Approval
Aug 22, 2016

Title
Regions-of-Interest Detection in big histopathological images

Summary
Although the ROI detection is just a preprocessing step for other CAD applications, due to the sheer volume and size of the whole slide images, the ROI detection is still a very difficult problem in such field. This project includes a new superpixel-driven segmentation algorithm to do segmentation on big images over 30000*30000 pixels in just several seconds. Also, it will research the parallel processing of multiple images. Thirdly, it will encompass features extraction and classification.

Aims

This projects aims to do ROI detection of the whole slide images fast and accurately.

Collaborators

Ishfaq Ahmad, Professor at University of Texas at Arlington.