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High-precision label-free virtual H&E staining of 3D holotomography using DAPI-guided conditional diffusion learning.

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Bibliographic Details
Title: High-precision label-free virtual H&E staining of 3D holotomography using DAPI-guided conditional diffusion learning.
Authors: Bak T; Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea., Kim S; Department of Nuclear Engineering, UNIST, Ulsan, 44919, Republic of Korea.; University of Toronto, Toronto, M5S 1A1, Canada., Ahn D; Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea.; Tomocube Inc., Daejeon, 34109, Republic of Korea., Min HS; Tomocube Inc., Daejeon, 34109, Republic of Korea. hsmin@tomocube.com., Lee J; Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea. jiminlee@unist.ac.kr.; Department of Nuclear Engineering, UNIST, Ulsan, 44919, Republic of Korea. jiminlee@unist.ac.kr.
Source: International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2026 May 05. Date of Electronic Publication: 2026 May 05.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: Germany NLM ID: 101499225 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1861-6429 (Electronic) Linking ISSN: 18616410 NLM ISO Abbreviation: Int J Comput Assist Radiol Surg Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1861-6429
DOI:10.1007/s11548-026-03651-x