2 citations · 2 across the 9 of their papers we have counts for
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Clinical Interpretability of Deep Learning Segmentation Through Shapley-Derived Agreement and Uncertainty Metrics
Tianyi Ren, Daniel Low, Pittra Jaengprajak +3
Segmentation is the identification of anatomical regions of interest, such as organs, tissue, and lesions, serving as a fundamental task in computer-aided diagnosis in medical imag…
Clinically-Informed Preprocessing Improves Stroke Segmentation in Low-Resource Settings
Juampablo E. Heras Rivera, Hitender Oswal, Tianyi Ren +4
Stroke is among the top three causes of death worldwide, and accurate identification of ischemic stroke lesion boundaries from imaging is critical for diagnosis and treatment. The…
How We Won the ISLES'24 Challenge by Preprocessing
Tianyi Ren, Juampablo E. Heras Rivera, Hitender Oswal +4
Stroke is among the top three causes of death worldwide, and accurate identification of stroke lesion boundaries is critical for diagnosis and treatment. Supervised deep learning m…
Here Comes the Explanation: A Shapley Perspective on Multi-contrast Medical Image Segmentation
Tianyi Ren, Juampablo Heras Rivera, Hitender Oswal +4
Deep learning has been successfully applied to medical image segmentation, enabling accurate identification of regions of interest such as organs and lesions. This approach works e…