由 Gus Iversen
, Editor in Chief | March 29, 2017
Royal Philips and PathAI, a developer of artificial intelligence technology for pathology, are collaborating to improve the accuracy and speed of routine clinical diagnosis in the lab.
Together, the companies are setting out to build practical deep learning applications that can be applied to massive pathology data sets to better inform interpretations and treatment decisions. The initial focus will be on breast cancer, and automatically detecting and quantifying cancerous lesions.
"Computational pathology can help pathologists mine richer information from the tissue sample than possible with the naked eye alone," Russ Granzow, general manager of Philips Digital Pathology Solutions, told HCB News. "Improved scanning, storing and processing have made it possible to pursue the big mission of applying computational techniques such as advanced image analytics tools to pathology."
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PathAI is a natural fit for this undertaking, having won the Camelyon Grand Challenge in Biomedical Image Analysis last year by showing their software could detect metastatic lesions in lymph nodes with a success rate that consistently rivaled human error.
“Our goal is to help patients receive fast, accurate diagnosis and support treating physicians to deliver optimal care by empowering pathologists with decision support tools powered by artificial intelligence,” said Dr. Andy Beck, company CEO, in a statement. "For example, identifying the presence or absence of cancer in lymph nodes is a routine and critically important task for a pathologist."
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Historically, pathologists have manually reviewed and analyzed tumor tissue slides using a microscope, but the rising shortage of pathologists and the increase in cancer caseloads make digital pathology a logical alternative for improving diagnostic accuracy and speed.
Philips has already implemented deep learning in its clinical informatics solutions for radiology such as Illumeo and IntelliSpace Portal 9.0.
Last year the company announced the acquisition
of PathXL, a successful Belfast-based startup, to help propel providers toward making the switch to digital image-based pathology workflows.