21 citations · 23 across the 7 of their papers we have counts for
9 papers
Combined Diffusion-Relaxation MRI to Assess Muscle Microstructure and Composition
Matteo Figini, Paddy J. Slator, Valeria E. Contarino +3
Quantifying muscle tissue properties is crucial for understanding pathophysiological changes occurring in skeletal muscle (SM). In particular, T2 relaxation and diffusion MRI (dMRI…
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…
Dual Deep Learning Approach for Non-invasive Renal Tumour Subtyping with VERDICT-MRI
Snigdha Sen, Lorna Smith, Lucy Caselton +6
This work aims to characterise renal tumour microstructure using diffusion MRI (dMRI); via the Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT)-M…
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…
Beyond Deterministic Translation for Unsupervised Domain Adaptation
Eleni Chiou, Eleftheria Panagiotaki, Iasonas Kokkinos
In this work we challenge the common approach of using a one-to-one mapping ('translation') between the source and target domains in unsupervised domain adaptation (UDA). Instead,…
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…