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Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification., , , , , and . IEEE Access, (2020)Automatic detection of pleural effusion in chest radiographs., , , , , , , and . Medical Image Anal., (2016)Handling label noise through model confidence and uncertainty: application to chest radiograph classification., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 1095016. SPIE, (2019)Automatic Pulmonary Artery-Vein Separation and Classification in Computed Tomography Using Tree Partitioning and Peripheral Vessel Matching., , , , , and . IEEE Trans. Medical Imaging, 35 (3): 882-892 (2016)Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box., , , , , , , , and . Medical Image Anal., 26 (1): 195-202 (2015)Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images., , , , , , , , , and 1 other author(s). Medical Image Anal., 18 (2): 374-384 (2014)SubSolid Nodules in lung cancer screening.. Utrecht University, Netherlands, (2014)base-search.net (ftunivutrecht:oai:dspace.library.uu.nl:1874/298095).Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images., , , , , , and . IEEE Trans. Medical Imaging, 34 (4): 962-973 (2015)Nodule detection and generation on chest X-rays: NODE21 Challenge., , , , , , , , , and 9 other author(s). CoRR, (2024)Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge., , , , , , , , , and 21 other author(s). CoRR, (2016)