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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Detalles Bibliográficos
Autores principales: Chen, Wen-Fan, Ou, Hsin-You, Pan, Cheng-Tang, Liao, Chien-Chang, Huang, Wen, Lin, Han-Yu, Cheng, Yu-Fan, Wei, Chia-Po
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470617/
https://www.ncbi.nlm.nih.gov/pubmed/34573941
http://dx.doi.org/10.3390/diagnostics11091599

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470617/
https://www.ncbi.nlm.nih.gov/pubmed/34573941
http://dx.doi.org/10.3390/diagnostics11091599

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