2 documents found, page 1 of 1
Deep learning methods for automatic evaluation of delayed enhancement-MRI. The ...
Lalande, Alain; Chen, Zhihao; Pommier, Thibaut; Decourselle, Thomas; Qayyum, Abdul; Salomon, Michel; Ginhac, Dominique; Skandarani, YoussefA key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed 10 min after injection of the contrast agent, provides high contrast between viable and nonviable myocardium and is therefore a method of choice to evaluate the extent of MI....
Auto-segmentation for thoracic radiation treatment planning: A grand challenge ...
Yang, Jinzhong; Veeraraghavan, Harini; Armato, Samuel G.; Farahani, Keyvan; Kirby, Justin S.; Kalpathy-Kramer, Jayashree; van Elmpt, WouterThis report presents the methods and results of the Thoracic Auto-Segmentation Challenge organized at the 2017 Annual Meeting of American Association of Physicists in Medicine. The purpose of the challenge was to provide a benchmark dataset and platform for evaluating performance of autosegmentation methods of organs at risk (OARs) in thoracic CT images.