7 papers
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…
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…
Unsupervised Domain Adaptation with Semantic Consistency across Heterogeneous Modalities for MRI Prostate Lesion Segmentation
Eleni Chiou, Francesco Giganti, Shonit Punwani +2
Any novel medical imaging modality that differs from previous protocols e.g. in the number of imaging channels, introduces a new domain that is heterogeneous from previous ones. Th…
Morphological Change Forecasting for Prostate Glands using Feature-based Registration and Kernel Density Extrapolation
Qianye Yang, Tom Vercauteren, Yunguan Fu +7
Organ morphology is a key indicator for prostate disease diagnosis and prognosis. For instance, In longitudinal study of prostate cancer patients under active surveillance, the vol…
Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation
Eleni Chiou, Francesco Giganti, Shonit Punwani +2
The need for training data can impede the adoption of novel imaging modalities for learning-based medical image analysis. Domain adaptation methods partially mitigate this problem…