Computer Aided Diagnosis of Cardiovascular Diseases

(01.09.2006 - 31.01.2011)

Assessment of coronary CT angiograms for the diagnosis of cardiovascular diseases is a time consuming and demanding task, requiring a high degree of clincal experience. In order to support clinical personel, reducion of diagnosis times and the increase of diagnosis reliability, this project aims to develop methods for the automatic detection, analysis and evaluation of lesions in coronary CT data.
For this task, methods from the areas of pattern recocgnition, image processing, visualization and modelling will be used (e.g. detection of lesions using pattern recocgnition, visualization by model generation of the coronary vascular tree). Finally, the methods developed will undergo clinical evaluation.

Papers at LGDV

Multi-Scale Feature Extraction for Learning-Based Classification of Coronary Artery Stenosis
Multi-Scale Feature Extraction for Learning-Based Classification of Coronary Artery Stenosis
Learning-Based Detection of Stenotic Lesions in Coronary CT Data
Learning-Based Detection of Stenotic Lesions in Coronary CT Data
  • Matthias Teßmann, Fernando Vega-Higuera, Dominik Fritz, Michael Scheuering, Günther Greiner
  • Proceedings of Vision, Modeling, and Visualization 2008
  • 2008; S. 189-198; ISBN: 978-3-89838-609-8;
Robust Automatic Calcium Scoring for CT Coronary Angiography
Robust Automatic Calcium Scoring for CT Coronary Angiography
  • Matthias Teßmann, Fernando Vega-Higuera, Bernhard Bischoff, Jörg Hausleiter, Günther Greiner
  • Bildverarbeitung für die Medizin 2010 - Algorithmen, Systeme, Anwendungen (Informatik Aktuell)
  • 2010; S. 430-434;
Automatic Detection and Quantification of Coronary Calcium on 3D CT Angiography Data
Automatic Detection and Quantification of Coronary Calcium on 3D CT Angiography Data

Promoter

  • Siemens AG, Sector Healthcare, Computed Tomography

Coworkers