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Chest X-Ray Report Generation Through Fine-Grained Label Learning.

, , , , , , , , , , , and . MICCAI (2), volume 12262 of Lecture Notes in Computer Science, page 561-571. Springer, (2020)

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Chest x-ray generation and data augmentation for cardiovascular abnormality classification., , , and . Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 105741M. SPIE, (2018)Semi-supervised learning with generative adversarial networks for chest X-ray classification with ability of data domain adaptation., , , and . ISBI, page 1038-1042. IEEE, (2018)Universal multi-modal deep network for classification and segmentation of medical images., , , , and . ISBI, page 872-876. IEEE, (2018)Quality controlled segmentation to aid disease detection., , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-rays., , , , , , , , , and 2 other author(s). CoRR, (2019)Artificial intelligence for point of care radiograph quality assessment., , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109503K. SPIE, (2019)Automatic Detection of Similarities and Differences between Small bowel Polyps and Ulcers with a Data Mining Approach in Wireless Capsule Endoscopy Videos., , , and . Int. J. Artif. Intell. Tools, (2012)Detecting tuberculosis in radiographs using combined lung masks., , , and . EMBC, page 4978-4981. IEEE, (2012)Dissecting self-supervised learning methods for surgical computer vision., , , , , , , , , and 3 other author(s). Medical Image Anal., (August 2023)Chest X-Ray Report Generation Through Fine-Grained Label Learning., , , , , , , , , and 2 other author(s). MICCAI (2), volume 12262 of Lecture Notes in Computer Science, page 561-571. Springer, (2020)