Evaluation of a deep image-to-image network (DI2IN) auto-segmentation algorithm across a network of cancer centers

Rayn, K., Gupta, V., Mulinti, S., Clark, R., Magliari, A., Chaudhari, S., Garima, G., & Beriwal, S. (2024). Evaluation of a deep image-to-image network (DI2IN) auto-segmentation algorithm across a network of cancer centers. Journal of Cancer Research and Therapeutics, 20(3), 1020–1025. https://doi.org/10.4103/jcrt.jcrt_769_23
Authors:
Kareem Rayn
Vibhor Gupta
Suneetha Mulinti
Ryan Clark
Anthony Magliari
Suresh Chaudhari
G. Garima
Sushil Beriwal
Affiliated Authors:
Kareem Rayn
Columbia Affiliation:
Subjects:
Algorithms (MeSH)
Deep Learning (MeSH)
Radiotherapy Planning, Computer-Assisted (MeSH)
Organs at Risk (MeSH)
Deep Learning in Medical Image Analysis (OpenAlex Topic)
Radiomics in Medical Imaging Analysis (OpenAlex Topic)
Positron Emission Tomography Imaging in Oncology (OpenAlex Topic)
Author Keywords:
artificial intelligence
auto-contouring
auto-segmentation
contouring
organ at risk
segmentation
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Publication Type:
Article
Unique ID:
10.4103/jcrt.jcrt_769_23
PMID:
39023610
DOI:
10.4103/jcrt.jcrt_769_23
Journal:
Journal of Cancer Research and Therapeutics
Publication Date:
Data Source:
OpenAlex
Source Link:
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