187 citations · 214 across the 5 of their papers we have counts for
7 papers · 1 filter
Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations
Gerda Bortsova, Florian Dubost, Laurens Hogeweg +2
The scarcity of labeled data often limits the application of supervised deep learning techniques for medical image segmentation. This has motivated the development of semi-supervis…
Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation
Shuai Chen, Gerda Bortsova, Antonio Garcia-Uceda Juarez +2
We propose a novel semi-supervised image segmentation method that simultaneously optimizes a supervised segmentation and an unsupervised reconstruction objectives. The reconstructi…
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…
Deep Learning from Label Proportions for Emphysema Quantification
Gerda Bortsova, Florian Dubost, Silas Ørting +5
We propose an end-to-end deep learning method that learns to estimate emphysema extent from proportions of the diseased tissue. These proportions were visually estimated by experts…
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…