142 citations · 1k across the 43 of their papers we have counts for
5 papers · 1 filter
Rician likelihood loss for quantitative MRI using self-supervised deep learning
Christopher S. Parker, Anna Schroder, Sean C. Epstein +3
Purpose: Previous quantitative MR imaging studies using self-supervised deep learning have reported biased parameter estimates at low SNR. Such systematic errors arise from the cho…
Learning transition times in event sequences: the Event-Based Hidden Markov Model of disease progression
Peter A. Wijeratne, Daniel C. Alexander
Progressive diseases worsen over time and are characterised by monotonic change in features that track disease progression. Here we connect ideas from two formerly separate methodo…
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…
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion
Ryutaro Tanno, Ardavan Saeedi, Swami Sankaranarayanan +2
The predictive performance of supervised learning algorithms depends on the quality of labels. In a typical label collection process, multiple annotators provide subjective noisy e…
Disease Knowledge Transfer across Neurodegenerative Diseases
Razvan V. Marinescu, Marco Lorenzi, Stefano B. Blumberg +8
We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal bio…