187 citations · 191 across the 4 of their papers we have counts for
9 papers
Adversarial Heart Attack: Neural Networks Fooled to Segment Heart Symbols in Chest X-Ray Images
Gerda Bortsova, Florian Dubost, Laurens Hogeweg +2
Adversarial attacks consist in maliciously changing the input data to mislead the predictions of automated decision systems and are potentially a serious threat for automated medic…
Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks
Florian Dubost, Benjamin Collery, Antonin Renaudier +5
Scoliosis is a condition defined by an abnormal spinal curvature. For diagnosis and treatment planning of scoliosis, spinal curvature can be estimated using Cobb angles. We propose…
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…