output
20082026
most citedNiftyNet: a deep-learning platform for medical imaging

563 citations

Showing 2020Show all

5 papers · 1 filter

q-bio.NC2020★ 9 cited

Focal to bilateral tonic-clonic seizures are associated with widespread network abnormality in temporal lobe epilepsy

Nishant Sinha, Natalie Peternell, Gabrielle M. Schroeder +6

Objective: To identify if whole-brain structural network alterations in patients with temporal lobe epilepsy (TLE) and focal to bilateral tonic-clonic seizures (FBTCS) differ from…

q-bio.NC2020★ 1 cited

Nonlinear computations in spiking neural networks through multiplicative synapses

Michele Nardin, James W Phillips, William F Podlaski +1

The brain efficiently performs nonlinear computations through its intricate networks of spiking neurons, but how this is done remains elusive. While nonlinear computations can be i…

cs.CV2020★ 28 cited

Scribble-based Domain Adaptation via Co-segmentation

Reuben Dorent, Samuel Joutard, Jonathan Shapey +7

Although deep convolutional networks have reached state-of-the-art performance in many medical image segmentation tasks, they have typically demonstrated poor generalisation capabi…

eess.IV2020★ 17 cited

Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and Semi-Supervised Learning

Fernando Pérez-García, Roman Rodionov, Ali Alim-Marvasti +3

Resective surgery may be curative for drug-resistant focal epilepsy, but only 40% to 70% of patients achieve seizure freedom after surgery. Retrospective quantitative analysis coul…

eess.IV2020★ 65 cited

Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI

Hari McGrath, Peichao Li, Reuben Dorent +6

Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. Current clinical practice is to measure the diameter of…