142 citations · 1k across the 43 of their papers we have counts for
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Degenerative Adversarial NeuroImage Nets for Brain Scan Simulations: Application in Ageing and Dementia
Daniele Ravi, Stefano B. Blumberg, Silvia Ingala +3
Accurate and realistic simulation of high-dimensional medical images has become an important research area relevant to many AI-enabled healthcare applications. However, current sta…
Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator
Hongxiang Lin, Matteo Figini, Ryutaro Tanno +10
MR images scanned at low magnetic field (T) have lower resolution in the slice direction and lower contrast, due to a relatively small signal-to-noise ratio (SNR) than those fr…
Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
Daniele Ravi, Daniel C. Alexander, Neil P. Oxtoby
Simulating images representative of neurodegenerative diseases is important for predicting patient outcomes and for validation of computational models of disease progression. This…
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
Felix J. S. Bragman, Ryutaro Tanno, Sebastien Ourselin +2
The performance of multi-task learning in Convolutional Neural Networks (CNNs) hinges on the design of feature sharing between tasks within the architecture. The number of possible…
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Ryutaro Tanno, Daniel Worrall, Enrico Kaden +6
Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, little consideration has been giv…
Multi-Stage Prediction Networks for Data Harmonization
Stefano B. Blumberg, Marco Palombo, Can Son Khoo +3
In this paper, we introduce multi-task learning (MTL) to data harmonization (DH); where we aim to harmonize images across different acquisition platforms and sites. This allows us…