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Frontiers in Artificial Intelligence|September 20, 2024
Noise-induced modality-specific pretext learning for pediatric chest X-ray image classificationSivaramakrishnan Rajaraman, Zhaohui Liang, Zhiyun Xue, et al.
Proceedings of Spie--The International Society for Optical Engineering|April 15, 2025
Ensembled YOLO for multiorgan detection in chest x-raysSivaramakrishnan Rajaraman, Zhaohui Liang, Zhiyun Xue, et al.
Studies in Health Technology and Informatics|September 14, 2004
Content-based image retrieval for large biomedical image archivesSameer Antani, L Rodney Long, George R Thoma
IEEE Access : Practical Innovations, Open Solutions|March 23, 2022
Trilateral Attention Network for Real-Time Cardiac Region SegmentationGhada Zamzmi, Sivaramakrishnan Rajaraman, Vandana Sachdev, et al.
New Microbes and New Infections|September 10, 2024
Automated quantification of SARS-CoV-2 pneumonia with large vision model knowledge adaptationZhaohui Liang, Zhiyun Xue, Sivaramakrishnan Rajaraman, et al.
Diagnostics (Basel, Switzerland)|January 18, 2020
Cross-Dataset Evaluation of Deep Learning Networks for Uterine Cervix SegmentationPeng Guo, Zhiyun Xue, L Rodney Long, et al.
Journal of Medical Systems|October 14, 2022
Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years ReviewK C Santosh, Siva Allu, Sivaramakrishnan Rajaraman, et al.
Frontiers in Genetics|March 14, 2022
Detecting Tuberculosis-Consistent Findings in Lateral Chest X-Rays Using an Ensemble of CNNs and Vision TransformersSivaramakrishnan Rajaraman, Ghada Zamzmi, Les R Folio, et al.
Radiology. Artificial Intelligence|December 6, 2021
Training Strategies for Radiology Deep Learning Models in Data-limited ScenariosSema Candemir, Xuan V Nguyen, Les R Folio, et al.
Plos One|March 31, 2022
DeBoNet: A deep bone suppression model ensemble to improve disease detection in chest radiographsSivaramakrishnan Rajaraman, Gregg Cohen, Lillian Spear, et al.
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