activity
20142023
most citedSynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining

641 citations · 1.8k across the 37 of their papers we have counts for

collaborators
Showing 2020Show all

10 papers · 1 filter

cs.CV2020

Active Annotation of Informative Overlapping Frames in Video Mosaicking Applications

Loic Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir +4

Video mosaicking requires the registration of overlapping frames located at distant timepoints in the sequence to ensure global consistency of the reconstructed scene. However, ful…

eess.IV2020

Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast

Juan Eugenio Iglesias, Benjamin Billot, Yael Balbastre +6

Most existing algorithms for automatic 3D morphometry of human brain MRI scans are designed for data with near-isotropic voxels at approximately 1 mm resolution, and frequently hav…

eess.IV2020★ 47 cited

DeepReg: a deep learning toolkit for medical image registration

Yunguan Fu, Nina Montaña Brown, Shaheer U. Saeed +14

DeepReg (https://github.com/DeepRegNet/DeepReg) is a community-supported open-source toolkit for research and education in medical image registration using deep learning.

cs.CV2020

3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology

Henry Tregidgo, Adria Casamitjana, Caitlin Latimer +9

Neuroimaging to neuropathology correlation (NTNC) promises to enable the transfer of microscopic signatures of pathology to in vivo imaging with MRI, ultimately enhancing clinical…

cs.CV2020★ 21 cited

Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis

Nalini M. Singh, Juan Eugenio Iglesias, Elfar Adalsteinsson +2

We propose neural network layers that explicitly combine frequency and image feature representations and show that they can be used as a versatile building block for reconstruction…

eess.IV2020★ 3 cited

An Auto-Encoder Strategy for Adaptive Image Segmentation

Evan M. Yu, Juan Eugenio Iglesias, Adrian V. Dalca +1

Deep neural networks are powerful tools for biomedical image segmentation. These models are often trained with heavy supervision, relying on pairs of images and corresponding voxel…