718 citations · 769 across the 12 of their papers we have counts for
14 papers · 1 filter
World of Forms: Deformable Geometric Templates for One-Shot Surface Meshing in Coronary CT Angiography
Rudolf L. M. van Herten, Ioannis Lagogiannis, Jelmer M. Wolterink +8
Deep learning-based medical image segmentation and surface mesh generation typically involve a sequential pipeline from image to segmentation to meshes, often requiring large train…
Nodule detection and generation on chest X-rays: NODE21 Challenge
Ecem Sogancioglu, Bram van Ginneken, Finn Behrendt +16
Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep lea…
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle +35
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Publ…
AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge
Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard +33
The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effectiv…
Deep Learning for Chest X-ray Analysis: A Survey
Ecem Sogancioglu, Erdi Çallı, Bram van Ginneken +2
Recent advances in deep learning have led to a promising performance in many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are a…
Deep Learning with robustness to missing data: A novel approach to the detection of COVID-19
Erdi Çallı, Keelin Murphy, Steef Kurstjens +5
In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN (Denoising Fully Connected Network). Since…