Literature DB >> 22528059

Left ventricular myocardium segmentation on delayed phase of multi-detector row computed tomography.

I-Chen Tsai1, Yu-Len Huang, Po-Ting Liu, Min-Chi Chen.   

Abstract

RATIONALE AND
OBJECTIVES: Advanced ischemic heart disease is usually accompanied by left ventricular (LV) myocardial volume loss and an abnormal enhancing pattern on delayed phase of multi-detector row computed tomography (MDCT). To assist radiologists and physicians in estimating the LV myocardial volume on delayed phase, this paper proposes an adaptive segmentation method for contouring the myocardial region in the delayed-phase MDCT and for computing the volume.
MATERIALS AND METHODS: The proposed method uses an anisotropic diffusion filter as a preprocessing procedure to enhance contrast and reduce specks in MDCT imaging. This work picks the middle of mid-ventricular level image slices as the lead slice. The proposed method develops two contouring modes to sketch the myocardium contour on the lead slice. By establishing the obtained contours as the initial contours, the region-growing method is employed to identify the contour of the myocardial region for each slice. The convex-hull finding algorithm is then used to refine the extracted contour. Finally, the width properties of the myocardial region and the morphological operators are used to obtain the entire LV myocardial volume.
RESULTS: Twenty-seven healthy patients who had no symptoms of ischemic heart disease are examined to evaluate the performance of the proposed method. Compared with manual contours delineated by two experienced experts, the contouring results using computer simulation reveal that the proposed method reliably identifies contours similar to those obtained using manual sketching.
CONCLUSION: The proposed method provides robust contouring for the LV myocardium on delayed-phase MDCT. The potential role of this technique may substantially reduce the time required to sketch manually a precise contour with high stability.

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Mesh:

Year:  2012        PMID: 22528059     DOI: 10.1007/s11548-012-0688-3

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


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