期刊
2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020)
卷 -, 期 -, 页码 1289-1292出版社
IEEE
DOI: 10.1109/isbi45749.2020.9098647
关键词
Microsatellite instability; histopathology; deep residual learning
Microsatellite instability is an important clinical marker for various types of cancers and is related to patients' prognosis and response to immunotherapy. Currently, identifying microsatellite status relies on genetic tests, which are not widely accessible for every patient. We propose a novel pipeline to predict MSI directly from histology slides which represent the gold standard for cancer diagnosis and are ubiquitously available for cancer patients. Our method outperformed existing method on the uterine corpus endometrial carcinoma cohort in The Cancer Genome Atlas (AUC 0.73 vs. 0.56).
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