Maximizing T2-Only Prostate Cancer Localization from Expected Diffusion Weighted Imaging
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-weighted (T2w) MR sequences. Early machine learning attempts using only T2w images have shown promising diagnostic performance in segmenting radiologist-annotated lesions. Such uni-modal T2-only approaches deliver substantial clinical benefits by reducing costs and expertise required to acquire other sequences. This work investigates an arguably more challenging application using only T2w at inference, but to localize individual cancers based on independent histopathology labels. We formulate DWI images as a laten...
| Authors | Weixi Yi, Yipei Wang, Wen Yan et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 April 2026 |
| Last updated at source | 1 April 2026 |
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