Deep Learning-Based Image Analysis Model for Classification and Quantification of Multiple Histopathological Findings in Rat Testis and Epididymis.
Saved in:
| Title: | Deep Learning-Based Image Analysis Model for Classification and Quantification of Multiple Histopathological Findings in Rat Testis and Epididymis. |
|---|---|
| Authors: | Shimazaki T; Toxicology Research Laboratories, Shionogi & Co., Ltd., Yokohama, Japan., Garg R; AIRA Matrix Private Limited, Dosti Pinnacle, Thane, India., Samanta P; AIRA Matrix Private Limited, Dosti Pinnacle, Thane, India., Mohanty A; AIRA Matrix Private Limited, Dosti Pinnacle, Thane, India., Thomas T; AIRA Matrix Private Limited, Dosti Pinnacle, Thane, India., Muta K; Toxicology Research Laboratories, Shionogi & Co., Ltd., Yokohama, Japan., Yamada N; Toxicology Research Laboratories, Shionogi & Co., Ltd., Yokohama, Japan., Yasui Y; Toxicology Research Laboratories, Shionogi & Co., Ltd., Yokohama, Japan., Shoda T; Toxicology Research Laboratories, Shionogi & Co., Ltd., Yokohama, Japan. |
| Source: | Toxicologic pathology [Toxicol Pathol] 2026 Jun; Vol. 54 (4), pp. 307-320. Date of Electronic Publication: 2026 Apr 05. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Sage Publications Country of Publication: United States NLM ID: 7905907 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1533-1601 (Electronic) Linking ISSN: 01926233 NLM ISO Abbreviation: Toxicol Pathol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
