61 citations · 69 across the 4 of their papers we have counts for
5 papers
OccluNet: Spatio-Temporal Deep Learning for Occlusion Detection on DSA
Anushka A. Kore, Frank G. te Nijenhuis, Matthijs van der Sluijs +8
Accurate detection of vascular occlusions during endovascular thrombectomy (EVT) is critical in acute ischemic stroke (AIS). Interpretation of digital subtraction angiography (DSA)…
Label Refinement Network from Synthetic Error Augmentation for Medical Image Segmentation
Shuai Chen, Antonio Garcia-Uceda, Jiahang Su +4
Deep convolutional neural networks for image segmentation do not learn the label structure explicitly and may produce segmentations with an incorrect structure, e.g., with disconne…
Dynamic Coronary Roadmapping via Catheter Tip Tracking in X-ray Fluoroscopy with Deep Learning Based Bayesian Filtering
Hua Ma, Ihor Smal, Joost Daemen +1
Percutaneous coronary intervention (PCI) is typically performed with image guidance using X-ray angiograms in which coronary arteries are opacified with X-ray opaque contrast agent…
Fast Prospective Detection of Contrast Inflow in X-ray Angiograms with Convolutional Neural Network and Recurrent Neural Network
Hua Ma, Pierre Ambrosini, Theo van Walsum
Automatic detection of contrast inflow in X-ray angiographic sequences can facilitate image guidance in computer-assisted cardiac interventions. In this paper, we propose two diffe…
Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy
Pierre Ambrosini, Daniel Ruijters, Wiro J. Niessen +2
Augmenting X-ray imaging with 3D roadmap to improve guidance is a common strategy. Such approaches benefit from automated analysis of the X-ray images, such as the automatic detect…