Medical Optical Imaging and Virtual Microscopy Image Analysis
نویسندگان
چکیده
Pathologists diagnose and grade prostate cancer by examining tissue from needle biopsies on glass slides. The cancer's severity risk of metastasis are determined the Gleason grade, a score based organization morphology glands. For diagnostic work-up, pathologists first locate glands in whole biopsy core, -- if they detect assign grade. This time-consuming process is subject to errors significant inter-observer variability, despite strict criteria. paper proposes an automated workflow that follows pathologists' \textit{modus operandi}, isolating classifying multi-scale patches individual slide images (WSI) tissues using distinct steps: (1) two fully convolutional networks segment epithelium versus stroma gland boundaries, respectively; (2) classifier network separates benign at high magnification; (3) additional predicts each low magnification. Altogether, this provides gland-specific approach for grading we compare against other machine-learning-based methods.
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ژورنال
عنوان ژورنال: Lecture Notes in Computer Science
سال: 2022
ISSN: ['1611-3349', '0302-9743']
DOI: https://doi.org/10.1007/978-3-031-16961-8