Wednesday, 19 June 2019

New technology to improve tissue imaging


The issue: Even as digital pathology makes rapid advances worldwide -- with more physicians analyzing tissue images on "smart" computers to diagnose patients -- there are no reliable standards for the preparation and digitization of the tissue slides themselves.

That means poor quality slides get mixed in with clear and accurate slides, potentially confusing or misleading a computer program trying to learn what a cancerous cell looks like, for example.

Bioengineering researcher Anant Madabhushi and Andrew Janowczyk, a senior research fellow in Madabhushi's Center for Computational Imaging and Personal Diagnostics, have developed a program that they say will ensure the quality of digital images being used for diagnostic and research purposes.


The new tool incorporates a series of measurements and classifiers to help users flag corrupted images and help retain those that will aid technicians and physicians in their diagnoses.

The application is "open source" -- or free for anyone to use, modify and extend. It can be accessed through an online repository. It was developed by Janowczyk about 18 months ago after discovering what he believed to be a surprising number of poor-quality slides from the well-known Cancer Genome Atlas, home to more than 30,000 tissue slides of cancer samples.

See: Andrew Janowczyk, Ren Zuo, Hannah Gilmore, Michael Feldman, Anant Madabhushi. HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides. JCO Clinical Cancer Informatics, 2019; (3): 1 DOI: 10.1200/CCI.18.00157

Posted by Dr. Tim Sandle, Pharmaceutical Microbiology

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