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DuCTSNet: MA‑SAM based fully automated DCIS segmentation and radiomic phenotyping for patient risk stratification in the ECOG‑ACRIN E4112 trial

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Year: 2026
Type: conference-paper
Source: SPIE Medical Imaging: Computer-Aided Diagnosis
DOI: 10.1117/12.3084844
Authors: Aaron Sossin, Kalina Slavkova, Somit Jain, Arunima Sharma, Ruya Kang, Sarah Voter, Debosmita Biswas, Eric M. Cohen, Anum S. Kazerouni, Walter Mankowski, Savannah Partridge, Joseph A. Sparano, Seema A. Khan, Christopher E. Comstock, Constantine Gatsonis, Constance Lehman, Justin Romanoff, Antonio Wolff, Jon Steingrimsson, Habib Rahbar, Despina Kontos
Language: English

Topic: Radiomics and Machine Learning in Medical Imaging
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
SDG: Good health and well-being

Open Access status: closed
OpenAlex ID: W7128711576
FWCI:
Cites: 14
Cited by:
Related to: 10
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