5 papers
Fed-ComBat: A Generalized Federated Framework for Batch Effect Harmonization in Collaborative Studies
Santiago Silva, Ghiles Reguig, Neil P Oxtoby +2
The use of multi-centric analyses is crucial for obtaining sufficient sample sizes and representative clinical populations in experimental studies. In this setting, data harmonizat…
Multi-modal Variational Autoencoders for normative modelling across multiple imaging modalities
Ana Lawry Aguila, James Chapman, Andre Altmann
One of the challenges of studying common neurological disorders is disease heterogeneity including differences in causes, neuroimaging characteristics, comorbidities, or genetic va…
Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels
Liam F Chalcroft, Jiongqi Qu, Sophie A Martin +8
When developing deep neural networks for segmenting intraoperative ultrasound images, several practical issues are encountered frequently, such as the presence of ultrasound frames…
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young +93
We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international…
Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
Santiago Silva, Boris Gutman, Eduardo Romero +3
At this moment, databanks worldwide contain brain images of previously unimaginable numbers. Combined with developments in data science, these massive data provide the potential to…