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Re-orientation of the left ventricle’s long-axis cardiac SPECT images using a statistical recursive method

¹ Department of Nuclear Engineering & Physics, Amir-Kabir University of Technology, Tehran, Iran; ² Control & Intelligent Processing Center of Excellence, University of Tehran, Tehran, Iran

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Objectives: This study presents a novel approach for estimating the Left Ventricle's (LV) long axis orientation in cardiac SPECT images. We introduce a statistical and recurcive algorithm which employs a set of Hypothetical Paths (HP) constructed from the myocardial structure to calculate the LV's long axis orientation. Analytical simulation of LV images along with images from real subjects were used to evaluate the method accuracy. Results imply that the presented method can automatically and accurately estimate the LV orientation in cardiac SPECT images.

Methods: The myocardial structure was segmented by Fuuzy Clustering method in all transaxial slices of the SPECT images. An objective function was constructed from a set of statistical parameters extracted from the parallel HPs enclosed by the myocardium. These objective functions were calculated for both transversal and sagittal orientations of the LV’s. Using a recursive algorithm, the objective function was minimized to estimate the transversal and sagittal orientations of the LVs. To evaluate the accuracy of the method, ischemic and fixed defect patterns (normal, mild and severe ischemia) of 40 patients were mapped on an analytical LV model with different orientations.

Results: Results(r=76, p<0.005)imply that the presented method is capable of estimating the LV's long axis orientaion automatically from cardiac SPECT images.

Conclusions: This study shows that this method has a good potential to accurately estimate the LV's long axis orientation in presence of cardiac diseases(fixed defect and ischemia).

Research Support: This study was supported by Physics and Nuclear Enginering Dept. of Amirkabir University of Technology.

This Article Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Bagher-Ebadian, H. Articles by Setayeshi, S. PubMed Articles by Bagher-Ebadian, H. Articles by Setayeshi, S.