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Implementation and Practice of Deep Learning-Based Instance Segmentation Algorithm for Quantification of Hepatic Fibrosis at Whole Slide Level in Sprague-Dawley Rats.
Hwang, Ji-Hee; Kim, Hyun-Ji; Park, Heejin; Lee, Byoung-Seok; Son, Hwa-Young; Kim, Yong-Bum; Jun, Sang-Yeop; Park, Jong-Hyun; Lee, Jaeku; Cho, Jae-Woo.
Affiliation
  • Hwang JH; Toxicologic Pathology Research Group, Department of Advanced Toxicology Research, Korea Institute of Toxicology, Daejeon, Korea.
  • Kim HJ; Toxicologic Pathology Research Group, Department of Advanced Toxicology Research, Korea Institute of Toxicology, Daejeon, Korea.
  • Park H; College of Veterinary Medicine, Chungnam National University, Daejeon, Korea.
  • Lee BS; Toxicologic Pathology Research Group, Department of Advanced Toxicology Research, Korea Institute of Toxicology, Daejeon, Korea.
  • Son HY; Toxicologic Pathology Research Group, Department of Advanced Toxicology Research, Korea Institute of Toxicology, Daejeon, Korea.
  • Kim YB; College of Veterinary Medicine, Chungnam National University, Daejeon, Korea.
  • Jun SY; Department of Advanced Toxicology Research, Korea Institute of Toxicology, Daejeon, Korea.
  • Park JH; Research & Development Team, LAC Inc, Seoul, Korea.
  • Lee J; Research & Development Team, LAC Inc, Seoul, Korea.
  • Cho JW; Research & Development Team, LAC Inc, Seoul, Korea.
Toxicol Pathol ; 50(2): 186-196, 2022 02.
Article in En | MEDLINE | ID: mdl-34866512
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Full text: 1 Database: MEDLINE Main subject: Deep Learning Type of study: Prognostic_studies Limits: Animals Language: En Year: 2022 Type: Article
Fulltext
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Full text: 1 Database: MEDLINE Main subject: Deep Learning Type of study: Prognostic_studies Limits: Animals Language: En Year: 2022 Type: Article