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Transactions on Machine Learning Research
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June 29, 2026
Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation
Aneesh Rangnekar, Harini Veeraraghavan
Proceedings of Spie--The International Society for Optical Engineering
|
April 9, 2026
Random forest-based out-of-distribution detection for robust lung cancer segmentation
Aneesh Rangnekar, Harini Veeraraghavan
Proceedings of Machine Learning Research
|
May 25, 2026
Co-distilled attention guided masked image modeling with noisy teacher for self-supervised learning on medical images
Jue Jiang, Aneesh Rangnekar, Harini Veeraraghavan
Medical Physics
|
December 5, 2024
Self-supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences
Jue Jiang, Aneesh Rangnekar, Harini Veeraraghavan
Proceedings of Spie--The International Society for Optical Engineering
|
October 20, 2025
Quantifying uncertainty in lung cancer segmentation with foundation models applied to mixed-domain datasets
Aneesh Rangnekar, Nishant Nadkarni, Jue Jiang, et al.
Proceedings of Spie--The International Society for Optical Engineering
|
April 15, 2026
Topological data analysis visualization for interpretable assessment of AI contouring quality
Chloe M S Choi, Aneesh Rangnekar, Jue Jiang, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging
|
June 16, 2026
DUAL CROSS-ATTENTION SIAMESE TRANSFORMER FOR RECTAL TUMOR REGROWTH ASSESSMENT IN WATCH-AND-WAIT ENDOSCOPY
Jorge Tapias Gomez, Despoina Kanata, Aneesh Rangnekar, et al.
Proceedings of Spie--The International Society for Optical Engineering
|
September 29, 2025
Swin transformers are robust to distribution and concept drift in endoscopy-based longitudinal rectal cancer assessment
Jorge Tapias Gomez, Aneesh Rangnekar, Hannah Williams, et al.
Physics and Imaging in Radiation Oncology
|
June 15, 2026
Transformer-based cardiac substructure segmentation from contrast and non-contrast computed tomography for radiotherapy planning
Aneesh Rangnekar, Nikhil Mankuzhy, Jonas Willmann, et al.
Annals of Surgical Oncology
|
May 3, 2024
Assessing Endoscopic Response in Locally Advanced Rectal Cancer Treated with Total Neoadjuvant Therapy: Development and Validation of a Highly Accurate Convolutional Neural Network
Hannah Williams, Hannah M Thompson, Christina Lee, et al.
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Showing results (1-10 of 12) with videos related to
Sort By:
Page
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Transactions on Machine Learning Research
|
June 29, 2026
Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation
Aneesh Rangnekar, Harini Veeraraghavan
Proceedings of Spie--The International Society for Optical Engineering
|
April 9, 2026
Random forest-based out-of-distribution detection for robust lung cancer segmentation
Aneesh Rangnekar, Harini Veeraraghavan
Proceedings of Machine Learning Research
|
May 25, 2026
Co-distilled attention guided masked image modeling with noisy teacher for self-supervised learning on medical images
Jue Jiang, Aneesh Rangnekar, Harini Veeraraghavan
Medical Physics
|
December 5, 2024
Self-supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences
Jue Jiang, Aneesh Rangnekar, Harini Veeraraghavan
Proceedings of Spie--The International Society for Optical Engineering
|
October 20, 2025
Quantifying uncertainty in lung cancer segmentation with foundation models applied to mixed-domain datasets
Aneesh Rangnekar, Nishant Nadkarni, Jue Jiang, et al.
Proceedings of Spie--The International Society for Optical Engineering
|
April 15, 2026
Topological data analysis visualization for interpretable assessment of AI contouring quality
Chloe M S Choi, Aneesh Rangnekar, Jue Jiang, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging
|
June 16, 2026
DUAL CROSS-ATTENTION SIAMESE TRANSFORMER FOR RECTAL TUMOR REGROWTH ASSESSMENT IN WATCH-AND-WAIT ENDOSCOPY
Jorge Tapias Gomez, Despoina Kanata, Aneesh Rangnekar, et al.
Proceedings of Spie--The International Society for Optical Engineering
|
September 29, 2025
Swin transformers are robust to distribution and concept drift in endoscopy-based longitudinal rectal cancer assessment
Jorge Tapias Gomez, Aneesh Rangnekar, Hannah Williams, et al.
Physics and Imaging in Radiation Oncology
|
June 15, 2026
Transformer-based cardiac substructure segmentation from contrast and non-contrast computed tomography for radiotherapy planning
Aneesh Rangnekar, Nikhil Mankuzhy, Jonas Willmann, et al.
Annals of Surgical Oncology
|
May 3, 2024
Assessing Endoscopic Response in Locally Advanced Rectal Cancer Treated with Total Neoadjuvant Therapy: Development and Validation of a Highly Accurate Convolutional Neural Network
Hannah Williams, Hannah M Thompson, Christina Lee, et al.
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