215 citations · 613 across the 19 of their papers we have counts for
19 papers
Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans
Zohaib Salahuddin, Matthias Lenga, Hannes Nickisch
We propose a deep learning-based automatic coronary artery tree centerline tracker (AuCoTrack) extending the vessel tracker by Wolterink (arXiv:1810.03143). A dual pathway Convolut…
Smart Chest X-ray Worklist Prioritization using Artificial Intelligence: A Clinical Workflow Simulation
Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch +5
The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTAT) for criti…
Learning a sparse database for patch-based medical image segmentation
Moti Freiman, Hannes Nickisch, Holger Schmitt +4
We introduce a functional for the learning of an optimal database for patch-based image segmentation with application to coronary lumen segmentation from coronary computed tomograp…
Improving CCTA based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation
Moti Freiman, Hannes Nickisch, Sven Prevrhal +5
Purpose: The goal of this study was to assess the potential added benefit of accounting for partial volume effects (PVE) in an automatic coronary lumen segmentation algorithm from…
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction
William Herlands, Daniel B. Neill, Hannes Nickisch +1
Identifying changes in model parameters is fundamental in machine learning and statistics. However, standard changepoint models are limited in expressiveness, often addressing unid…
When does Bone Suppression and Lung Field Segmentation Improve Chest X-Ray Disease Classification?
Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich +6
Chest radiography is the most common clinical examination type. To improve the quality of patient care and to reduce workload, methods for automatic pathology classification have b…