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Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches.

, , , , and . IEEE Trans. Medical Imaging, 38 (8): 1777-1787 (2019)

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Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning., , , and . IPMI, volume 10265 of Lecture Notes in Computer Science, page 249-260. Springer, (2017)Supervised and Unsupervised Tumor Characterization in the Deep Learning Era., , , , , and . CoRR, (2018)Estimation of BMI from facial images using semantic segmentation based region-aware pooling., , and . Comput. Biol. Medicine, (2021)Deep Detector Health Management under Adversarial Campaigns., , , , , , and . CoRR, (2019)A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation., , , , , , , , , and . IEEE Trans. Biomed. Eng., 66 (4): 1069-1081 (2019)Deep multi-modal classification of intraductal papillary mucinous neoplasms (IPMN) with canonical correlation analysis., , , , , and . ISBI, page 800-804. IEEE, (2018)Context Driven Label Fusion for segmentation of Subcutaneous and Visceral Fat in CT Volumes., , , , , and . CoRR, (2015)How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis., , , and . CoRR, (2017)Out of distribution detection for skin and malaria images., , , , , and . CoRR, (2021)TumorNet: Lung nodule characterization using multi-view Convolutional Neural Network with Gaussian Process., , , , and . ISBI, page 1007-1010. IEEE, (2017)