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## Introduction
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<div style="text-align: justify; width: 100%;">
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This repository presents an auto-contouring algorithm [??] segmenting the entire heart, including its chambers and coronary arteries. This algorithm was trained on 560 thoracic planning computed tomography (CT) scans from Brigham and Women’s Hospital/Dana-Farber Cancer Institute and internally validated on 70 additional cases. External validation was conducted on 283 patients with lung or breast cancer treated at Cedars-Sinai Medical Center (2005-2020). This auto-contouring algorithm segments the whole heart, the heart chambers (LA, LV, RA, RV) and the heart coronaries (LAD, LCX, LM, PDA, RCA). </div>
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This repository presents an auto-contouring algorithm [1] segmenting the entire heart, including its chambers and coronary arteries. This algorithm was trained on 560 thoracic planning computed tomography (CT) scans from Brigham and Women’s Hospital/Dana-Farber Cancer Institute and internally validated on 70 additional cases. External validation was conducted on 283 patients with lung or breast cancer treated at Cedars-Sinai Medical Center (2005-2020). This auto-contouring algorithm segments the whole heart, the heart chambers (LA, LV, RA, RV) and the heart coronaries (LAD, LCX, LM, PDA, RCA). </div>
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Please refer to [modelLabels.csv](ROCardS/data/labels/modelLabels.csv) for additional details on the algorithm segments.
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## References
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[1] main paper ref
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[1] Guthier C. *et al.* Clinical Validation and Prospective Deployment of an Automated Deep
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Learning-Based Coronary Segmentation and Cardiac Toxicity Risk Prediction
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System.
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[3] Fedorov A. *et al.* NCI Imaging Data Commons. Cancer Res. 81, 4188–4193 (2021).

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