3 papers
eess.IV2026
Ultra-Strong Gradient Diffusion MRI with Self-Supervised Learning for Prostate Cancer Characterization
Tanishq Patil, Snigdha Sen, Kieran G. Foley +7
Diffusion MRI (dMRI) enables non-invasive assessment of prostate microstructure but conventional dMRI metrics such as the Apparent Diffusion Coefficient in multiparametric MRI and…
eess.IV2024
MRI Parameter Mapping via Gaussian Mixture VAE: Breaking the Assumption of Independent Pixels
Moucheng Xu, Yukun Zhou, Tobias Goodwin-Allcock +4
We introduce and demonstrate a new paradigm for quantitative parameter mapping in MRI. Parameter mapping techniques, such as diffusion MRI and quantitative MRI, have the potential…
eess.IV2023
ssVERDICT: Self-Supervised VERDICT-MRI for Enhanced Prostate Tumour Characterisation
Snigdha Sen, Saurabh Singh, Hayley Pye +6
Purpose: Demonstrating and assessing self-supervised machine learning fitting of the VERDICT (Vascular, Extracellular and Restricted DIffusion for Cytometry in Tumours) model for p…