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.
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