Left ventricle segmentation in dynamic cardiac CT using random walks method.

Purpose: Segmentation of the left ventricle (LV) in cardiac CT (CCT) images is difficult due to the intensity heterogeneity arising from accumulation of contrast agent in papillary muscle and trabeculae carneae. In this study, we demonstrated the random walks method for LV segmentation in CCT through cardiac phases.

Methods: 63 CCT data sets from 7 patients with 9 cardiac phases were included in this study. All cardiac CT examinations were performed with GE 64-detector CT scanner with ECG gating. In each patient, 60-80 ml iohexol was injected at a flow rate of 5 ml/sec followed by 60 ml normal saline solution. Random walks (RW) based on probability of labels was used for LV segmentation. The LV delineations generated by the experienced physician (MD), conventional image-based method (IB), and RW were compared.

Results: In general the contours segment the LV closely by RW and MD, but the discrepancies in papillary muscle and trabeculae carneae were observed while using the IB method.

Conclusion: We showed the RW method potentially improved LV segmentation as compared to the volume by conventional IB method. In this study, we demonstrated the clinical feasibility of LV volume segmentation using random walks algorithm.