Doctor’s Can Identify Cancer Cells with Help of AI

Anju Bisht

, News & Research
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A powerful way of predicting patient outcome. Researchers have developed a software tool that uses Artificial Intelligence (AI) to recognize cancer cells from digital pathology images.

 

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The spatial distribution of different types of cells can reveal cancer’s growth pattern and their relation with the surrounding micro-environment as well as the body’s immune response.

 

The manual process of identifying all the cells in a pathology slide is extremely labor-intensive plus error-prone as well.

 

The corresponding author of a study published in E-bioMedicine, Dr. Guanghua “Andy” Xiao said, “To make a diagnosis, pathologists usually only examine several ‘representative’ regions in detail, rather than the whole slide. However, some important details could be missed by this approach.”

 

How to automatically classify different types of cells and quantify their spatial distributions is a major technical challenge in systematically studying the tumor micro-environment.

 

To overcomes these obstacles by using AI to classify cell types from lung cancer pathology images. The AI algorithm that Dr. Xiao and his team developed, called “ConvPath”.

 

AI algorithm learns from human pathologists. The algorithm can look at cells and identify their types based on their appearance in the pathology images.

 

The pathologists can obtain the most accurate cancer cell analysis in a much faster way with the help of the algorithm.

 

Dr. Xiao said, “It is time-consuming and difficult for pathologists to locate very small tumor regions in tissue images, so this could greatly reduce the time that pathologists need to spend on each image.”

 

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