6 citations · 6 across the 5 of their papers we have counts for
6 papers
Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021
Carole H. Sudre, Kimberlin Van Wijnen, Florian Dubost +46
Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and…
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…
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…
Hydranet: Data Augmentation for Regression Neural Networks
Florian Dubost, Gerda Bortsova, Hieab Adams +4
Deep learning techniques are often criticized to heavily depend on a large quantity of labeled data. This problem is even more challenging in medical image analysis where the annot…
3D Regression Neural Network for the Quantification of Enlarged Perivascular Spaces in Brain MRI
Florian Dubost, Hieab Adams, Gerda Bortsova +4
Enlarged perivascular spaces (EPVS) in the brain are an emerging imaging marker for cerebral small vessel disease, and have been shown to be related to increased risk of various ne…
GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network
Florian Dubost, Gerda Bortsova, Hieab Adams +4
We propose a novel convolutional neural network for lesion detection from weak labels. Only a single, global label per image - the lesion count - is needed for training. We train a…