activity
20172022
most citedLongitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration

23 citations · 37 across the 13 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

eess.IV2019★ 6 cited

A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes

Bo Li, Wiro Niessen, Stefan Klein +4

To accurately analyze changes of anatomical structures in longitudinal imaging studies, consistent segmentation across multiple time-points is required. Existing solutions often in…

eess.IV2019

Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset

Bo Li, Marius de Groot, Meike Vernooij +3

Tract-specific diffusion measures, as derived from brain diffusion MRI, have been linked to white matter tract structural integrity and neurodegeneration. As a consequence, there i…

eess.IV2019

Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network

Kimberlin M. H. van Wijnen, Florian Dubost, Pinar Yilmaz +5

Localization of focal vascular lesions on brain MRI is an important component of research on the etiology of neurological disorders. However, manual annotation of lesions can be ch…

eess.IV2019

Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation

Florian Dubost, Marleen de Bruijne, Marco Nardin +10

Registration is a core component of many imaging pipelines. In case of clinical scans, with lower resolution and sometimes substantial motion artifacts, registration can produce po…

cs.CV2019

Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks

Florian Dubost, Hieab Adams, Pinar Yilmaz +6

Finding automatically multiple lesions in large images is a common problem in medical image analysis. Solving this problem can be challenging if, during optimization, the automated…