Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network.
Sci Rep
; 9(1): 16912, 2019 11 15.
Article
em En
| MEDLINE
| ID: mdl-31729459
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 images containing cancer cells. We extended the method to large-size image analysis enabling accurate detection of metastatic lesions. We discuss usefulness of DUV excitation fluorescence imaging with the aid of DNN analysis, which is promising for assisting pathologists in assessment of lymph node metastasis.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Redes Neurais de Computação
/
Linfonodos
/
Metástase Linfática
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Microscopia de Fluorescência
Tipo de estudo:
Diagnostic_studies
/
Guideline
Limite:
Humans
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2019
Tipo de documento:
Article