most citedDIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders

60 citations · 100 across the 5 of their papers we have counts for

collaborators

5 papers

physics.med-ph2019

Machine learning based white matter models with permeability: An experimental study in cuprizone treated in-vivo mouse model of axonal demyelination

Ioana Hill, Marco Palombo, Mathieu Santin +14

The intra-axonal water exchange time τi, a parameter associated with axonal permeability, could be an important biomarker for understanding demyelinating pathologies such as Multip…

physics.med-ph20191 cited

In utero diffusion MRI: challenges, advances, and applications

Daan Christiaens, Paddy J. Slator, Lucilio Cordero-Grande +6

In utero diffusion MRI provides unique opportunities to non-invasively study the microstructure of tissue during fetal development. A wide range of developmental processes, such as…

cs.LG201931 cited

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…

cs.CV201960 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…

physics.comp-ph20178 cited

Realistic voxel sizes and reduced signal variation in Monte-Carlo simulation for diffusion MR data synthesis

Matt G Hall, Gemma Nedjati-Gilani, Daniel C Alexander

To synthesize diffusion MR measurements from Monte-Carlo simulation using tissue models with sizes comparable to those of scan voxels. Larger regions enable restricting structures…