Identification of Early Esophageal Cancer by Semantic Segmentation.
Ontology highlight
ABSTRACT:
SUBMITTER: Fang YJ
PROVIDER: S-EPMC9331549 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
Publications
Identification of Early Esophageal Cancer by Semantic Segmentation.
Fang Yu-Jen YJ Mukundan Arvind A Tsao Yu-Ming YM Huang Chien-Wei CW Wang Hsiang-Chen HC
Journal of personalized medicine 20220725 8
Early detection of esophageal cancer has always been difficult, thereby reducing the overall five-year survival rate of patients. In this study, semantic segmentation was used to predict and label esophageal cancer in its early stages. U-Net was used as the basic artificial neural network along with Resnet to extract feature maps that will classify and predict the location of esophageal cancer. A total of 75 white-light images (WLI) and 90 narrow-band images (NBI) were used. These images were cl ...[more]
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