6 papers · 1 filter
Bridging Single Distortion Artifacts and Multifactorial Clinical Quality: Few-shot Biparametric MRI Quality Assessment via Distortion-trained Prototypical Networks
Yucheng Tang, Alexander Ng, Wen Yan +11
Clinical prostate multi-parametric MRI relies heavily on high-quality diffusion-weighted imaging (DWI), yet reading DWI is frequently compromised by geometric distortion, often cau…
Learning to Distort: Weakly-Supervised Image Quality Transfer for Prostate DWI Correction
YuCheng Tang, Wen Yan, Alexander Ng +13
Single-shot echo-planar prostate diffusion-weighted imaging (DWI) is frequently complicated by geometric distortions, which impact the ability to derive reliable diagnoses from suc…
Maximizing T2-Only Prostate Cancer Localization from Expected Diffusion Weighted Imaging
Weixi Yi, Yipei Wang, Wen Yan +10
Multiparametric MRI is increasingly recommended as a first-line noninvasive approach to detect and localize prostate cancer, requiring at minimum diffusion-weighted (DWI) and T2-we…
ProFound: A moderate-sized vision foundation model for multi-task prostate imaging
Yipei Wang, Yinsong Xu, Weixi Yi +11
Many diagnostic and therapeutic clinical tasks for prostate cancer increasingly rely on multi-parametric MRI. Automating these tasks is challenging because they necessitate expert…
Understanding the Transfer Limits of Vision Foundation Models
Shiqi Huang, Yipei Wang, Natasha Thorley +8
Foundation models leverage large-scale pretraining to capture extensive knowledge, demonstrating generalization in a wide range of language tasks. By comparison, vision foundation…
Impact of Clinical Image Quality on Efficient Foundation Model Finetuning
Yucheng Tang, Pawel Rajwa, Alexander Ng +11
Foundation models in medical imaging have shown promising label efficiency, achieving high performance on downstream tasks using only a fraction of the annotated data otherwise req…