Deep learning model targeting cancer surrounding tissues for accurate cancer diagnosis based on histopathological images.

ABSTRACT: Accurate and fast histological diagnosis of cancers is crucial for successful treatment. The deep learning-based approaches have assisted pathologists in efficient cancer diagnosis. The remodeled microenvironment and field cancerization may enable the cancer-specific features in the image of non-cancer regions surrounding cancer, which may provide additional information not available in the cancer region to improve cancer diagnosis. Here, we proposed a deep learning framework with fine-tuning target proportion towards cancer surrounding tissues in histological images for gastric cancer diagnosis. Through employing six deep learning-based models targeting region-of-interest (ROI) with different proportions of no-cancer and cancer regions, we uncovered the diagnostic value of non-cancer ROI,

SUBMITTER: Li L 

PROVIDER: S-EPMC11755804 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature