activity
20042026
most citedTADPOLE Challenge: Prediction of Longitudinal Evolution in Alzheimer's Disease

100 citations · 471 across the 32 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

eess.IV2019

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…

eess.IV2019

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…

q-bio.NC2019

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

Neil P. Oxtoby, Fabio S. Ferreira, Agoston Mihalik +12

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions acr…

q-bio.NC2019

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression

Agoston Mihalik, Mikael Brudfors, Maria Robu +12

We applied several regression and deep learning methods to predict fluid intelligence scores from T1-weighted MRI scans as part of the ABCD Neurocognitive Prediction Challenge (ABC…

cs.CV2019★ 60 cited

DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders

Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi +5

Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-te…

cs.LG2019

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…