Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network.

ABSTRACT: Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopathology based on hematoxylin and eosin (H&E) staining. We established a fluorescent staining protocol for DUV excitation fluorescence imaging that has enabled clear discrimination of nucleoplasm, nucleolus, and cytoplasm. Fluorescence images of metastasis-positive/-negative lymph nodes of gastric cancer patients were used for patch-based training with a deep neural network (DNN) based on Inception-v3 architecture. The performance on small patches of the fluorescence images was comparable with that of H&E images. Gradient-weighted class activation mapping analysis revealed the areas where the trained model identified metastatic lesions in the image

SUBMITTER: Matsumoto T 

PROVIDER: S-EPMC6858352 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature