Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort.

Saved in:
Bibliographic Details
Title: Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort.
Authors: Skarsø ER; Danish Center for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark.; Department of Clinical medicine, Aarhus University, Aarhus, Denmark., Refsgaard L; Department of Clinical medicine, Aarhus University, Aarhus, Denmark.; Department of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus, Denmark., Saini A; Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Næstved, Denmark., Sloth Møller D; Department of Clinical medicine, Aarhus University, Aarhus, Denmark.; Department of Oncology, Aarhus University Hospital, Aarhus, Denmark., Lorenzen EL; Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark., Maae E; Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, Vejle, Denmark., Andersen K; Department of Oncology, Herlev and Gentofte Hospital, Herlev, Denmark., Maraldo MV; Department of Clinical Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark., Milo ML; Department of Oncology, Aalborg University Hospital, Aalborg, Denmark., Nyeng TB; Department of Oncology, Aarhus University Hospital, Aarhus, Denmark., Vrou Offersen B; Danish Center for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark.; Department of Clinical medicine, Aarhus University, Aarhus, Denmark.; Department of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus, Denmark.; Department of Oncology, Aarhus University Hospital, Aarhus, Denmark., Korreman SS; Danish Center for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark.; Department of Clinical medicine, Aarhus University, Aarhus, Denmark.; Department of Oncology, Aarhus University Hospital, Aarhus, Denmark.
Source: Acta oncologica (Stockholm, Sweden) [Acta Oncol] 2023 Oct; Vol. 62 (10), pp. 1201-1207. Date of Electronic Publication: 2023 Sep 15.
Publication Type: Journal Article
Journal Info: Publisher: Medical Journals Sweden AB Country of Publication: Sweden NLM ID: 8709065 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1651-226X (Electronic) Linking ISSN: 0284186X NLM ISO Abbreviation: Acta Oncol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1651-226X
DOI:10.1080/0284186X.2023.2252582