Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort-Reference-Cited by-同舟云学术

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

Published:2023-09-15 Issue:10 Volume:62 Page:1201-1207
ISSN:0284-186X
Container-title:Acta Oncologica
language:en
Short-container-title:Acta Oncologica

Author:

Skarsø Emma Riis¹²^ORCID,Refsgaard Lasse²³,Saini Abhilasha⁴,Sloth Møller Ditte²⁵,Lorenzen Ebbe Laugaard⁶^ORCID,Maae Else⁷,Andersen Karen⁸,Maraldo Maja Vestmø⁹,Milo Marie Louise¹⁰,Nyeng Tine Bisballe⁵,Vrou Offersen Birgitte¹²³⁵,Korreman Stine Sofia¹²⁵

Affiliation:

1. Danish Center for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark

2. Department of Clinical medicine, Aarhus University, Aarhus, Denmark

3. Department of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus, Denmark

4. Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Næstved, Denmark

5. Department of Oncology, Aarhus University Hospital, Aarhus, Denmark

6. Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark

7. Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, Vejle, Denmark

8. Department of Oncology, Herlev and Gentofte Hospital, Herlev, Denmark

9. Department of Clinical Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark

10. Department of Oncology, Aalborg University Hospital, Aalborg, Denmark

Funder

Dansk Kræftforsknings Fond

PhD scholarship funding from Department of Clinical Medicine, Aarhus University

Publisher

Medical Journals Sweden AB

Subject

Radiology, Nuclear Medicine and imaging,Oncology,Hematology,General Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/0284186X.2023.2252582

Reference23 articles.

1. Effect of accurate heart delineation on cardiac dose during the CONVERT trial

2. Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery

3. Training, validation, and clinical implementation of a deep-learning segmentation model for radiotherapy of loco-regional breast cancer

4. Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer

5. The impact of training sample size on deep learning-based organ auto-segmentation for head-and-neck patients

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