115 citations · 138 across the 8 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…
Learning to Downsample for Segmentation of Ultra-High Resolution Images
Chen Jin, Ryutaro Tanno, Thomy Mertzanidou +2
Many computer vision systems require low-cost segmentation algorithms based on deep learning, either because of the enormous size of input images or limited computational budget. C…
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…
Combined Diffusion-Relaxometry MRI to Identify Dysfunction in the Human Placenta
Paddy J. Slator, Jana Hutter, Marco Palombo +7
Purpose: A combined diffusion-relaxometry MR acquisition and analysis pipeline for in-vivo human placenta, which allows for exploration of coupling between T2* and apparent diffusi…