Huron announces collaboration with UPMC and abstract presentation at Pathology Informatics Summit

Huron Digital Pathology announced today that Dr. Hamid Tizhoosh, Director of the KIMIA Lab at the University of Waterloo and Huron advisory board member, will present a talk entitled “Faster, Better, More Reliable than Deep Features: A Projection-Based, Pathologist-Centric Approach to Identification of Histopathology Images” at the Pathology Informatics Summit on May 22, 2018 in Pittsburgh, PA.

The company also announced its research collaboration with the University of Pittsburgh Medical Center (UPMC)and digital pathology pioneer, Dr. Liron Pantanowitz, Professor of Pathology & Biomedical Informatics and Director of Pathology Informatics at UPMC Shadyside, in the field of content-based image retrieval using artificial intelligence.

Dr. Tizhoosh’s abstract presentation at the Pathology Informatics Summit will be the first public introduction to Huron’s technology for identification and retrieval of histopathology images. He will describe a unique approach to image search that places the pathologist in the center of decision making,a key ingredient to driving adoption of artificial intelligence techniques in pathology. The abstract presentation will take place at 8:30am on Tuesday, May 22nd.

“Huron’s whole slide scanners generatepetabytes of image data each year, so itmade sense for us to develop a simple, yet powerfulway to search histopathology images and access underlying knowledge,” commented Patrick Myles, CEO of Huron Digital Pathology. “We are actively validating our technology through collaboration with leading clinical, research and academic institutions as well as key industry partners. We are particularly thrilled to be working with Dr. Pantanowitz,who is providing us withvaluable feedback andaccess to a rich digital pathology archive.”

Dr. Liron Pantanowitz, Professor of Pathology & Biomedical Informatics and Director of Pathology Informatics at UPMC Shadyside, commented:

Many of us have witnessed the value of reverse image lookup using Google Image Search. Unfortunately, such content-based image retrieval tools are not readily available for clinical use in pathology. However, it is hoped that future image algorithms, such as the technology Huron are developing today with UPMC and the University of Waterloo, will likely mature to the point of playing an important role in computer assisted diagnosis for anatomic pathology practice.

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