Automated coronary calcification detection and scoring

Ivana Išgum, Bram van Ginneken, Annemarieke Rutten, Mathias Prokop

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)

Abstract

An automated method for coronary calcification detection from ECG-triggered multi-slice CT data is presented. The method first segments the heart region. In the obtained volume candidate objects are extracted by thresholding. They include coronary calcification, calcium located elsewhere in the heart, for example, in the valves or the myocardium, and other high density structures mostly representing noise and bone. A set of 57 features is calculated for each candidate object. In the feature space objects are classified with a k-NN classifier and feature selection in three consecutive stages. The method is tested on 51 scans of the heart. They contain 320 calcification in the coronary arteries, 291 in the aorta and 62 calcifications in the heart. The system correctly detected 177 calcifications in the coronaries at the expense of 56 false positive objects. On average the method makes 3.8 errors per scan.
Original languageEnglish
Title of host publicationISPA 2005 - Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis
Pages127-132
Volume2005
Publication statusPublished - 2005
EventISPA 2005 - 4th International Symposium on Image and Signal Processing and Analysis - , Croatia
Duration: 15 Sep 200517 Sep 2005

Publication series

NameImage and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium

Conference

ConferenceISPA 2005 - 4th International Symposium on Image and Signal Processing and Analysis
Country/TerritoryCroatia
Period15/09/200517/09/2005

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