7 papers
SFL-Net: Source-Factorized Latent Representation Learning for Multi-Contrast MRI to Tau-PET Synthesis
Agamdeep S. Chopra, Caitlin Neher, Tianyi Ren +3
Tau positron emission tomography supports Alzheimer's disease staging but is difficult to scale because of tracer, scanner, and radiation constraints. Synthesis from structural MRI…
BTReport: A Framework for Brain Tumor Radiology Report Generation with Clinically Relevant Features
Juampablo E. Heras Rivera, Dickson T. Chen, Tianyi Ren +4
Recent advances in radiology report generation (RRG) have been driven by large paired image-text datasets; however, progress in neuro-oncology has been limited due to a lack of ope…
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…