Recognition Rate Advancement and Data Error Improvement of Pathology Cutting with H-DenseUNet for Hepatocellular Carcinoma Image

Recognition Rate Advancement and Data Error Improvement of Pathology Cutting with H-DenseUNet for Hepatocellular Carcinoma Image

Due to the fact that previous studies have rarely investigated the recognition rate discrepancy and pathology data error when applied to different databases, the purpose of this study is to investigate the improvement of recognition rate via deep learning-based liver lesion segmentation with the inc...

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Bibliographic Details
Main Authors: Wen-Fan Chen, Hsin-You Ou, Cheng-Tang Pan, Chien-Chang Liao, Wen Huang, Han-Yu Lin, Yu-Fan Cheng, Chia-Po Wei
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Diagnostics
Subjects:
data comparison
deep learning
H-DenseUNet
lesion segmentation
liver segmentation
medical statistics
Online Access:https://www.mdpi.com/2075-4418/11/9/1599

Internet

https://www.mdpi.com/2075-4418/11/9/1599

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