DocumentCode :
1739162
Title :
Automated left ventricle boundary delineation
Author :
Sui, Lei ; Haralick, Robert M. ; Sheehan, Florence H.
Author_Institution :
Dept. for Bioeng., Washington Univ., Seattle, WA, USA
fYear :
2000
fDate :
2000
Firstpage :
339
Lastpage :
346
Abstract :
Automated left ventricle (LV) boundary delineation from left ventriculograms has been studied for decades. Unfortunately, no methods in terms of the accuracy about volume and ejection fraction have ever been reported. A new knowledge based multi-stage method to automatically delineate the LV boundary at end diastole and end systole is discussed in this paper: It has a mean absolute boundary error of about 2 mm and an associated ejection fraction error of about 6%. The method makes extensive use of knowledge about LV shape and movement. The processing includes a multi-image pixel region classification, a shape regression and a rejection classification. The method was trained and tested on a database of 375 studies whose ED and ES boundary have been manually traced as the ground truth. The cross-validated results presented in this paper shows that the accuracy is close to and slightly above inter-observer variability
Keywords :
cardiology; diagnostic radiography; edge detection; image classification; medical image processing; automated left ventricle boundary delineation; end diastole; end systole; interobserver variability; knowledge based multi-stage method; mean absolute boundary error; medical diagnostic imaging; multi-image pixel region classification; rejection classification; shape regression; Biomedical engineering; Calibration; Cardiology; Filtering; Gaussian distribution; Humans; Image databases; Image edge detection; Shape; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Informatics and Biomedical Engineering, 2000. Proceedings. IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7695-0862-6
Type :
conf
DOI :
10.1109/BIBE.2000.889626
Filename :
889626
Link To Document :
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