Name
Title | ||
|---|---|---|
A complete system for automatic extraction of left ventricular myocardium from CT images using shape segmentation and contour evolution. |
Abstract | ||
|---|---|---|
The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TIP.2014.2300751 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
geometric characteristics,coarse-to-fine strategy,cardiology,computerised tomography,cardiac computed tomography,functional analysis,shape information,ct images,image segmentation,left ventricular myocardium,shape segmentation,automatic extraction,triangulated surface,automatic delineation,complete system,image intensities,contour evolution,myocardium segmentation,anatomical characteristics,entire circulation system,myocardial surfaces,left ventricle,medical image processing,blood pool,heart,shape | Computer vision,Pattern recognition,Segmentation,Image segmentation,Artificial intelligence,Ventricle,Computed tomography,Mathematics,Radiographic Image Enhancement,Left ventricular myocardium | Journal |
Volume | Issue | ISSN |
23 | 3 | 1941-0042 |
Citations | PageRank | References |
4 | 0.71 | 35 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liangjia Zhu | 1 | 92 | 9.07 |
| Yi Gao | 2 | 115 | 18.29 |
| Vikram Appia | 3 | 24 | 2.73 |
| Anthony J. Yezzi | 4 | 2016 | 151.48 |
| Chesnal Arepalli | 5 | 7 | 2.06 |
| Tracy L. Faber | 6 | 7 | 2.13 |
| Arthur Stillman | 7 | 4 | 1.04 |
| Allen Tannenbaum | 8 | 3629 | 409.15 |