Left ventricular boundary detection from spatio-temporal volumetric computed tomography images.
This paper presents a new automatic technique for left ventricle boundary detection from a set of three-dimensional (3D) computed tomography (CT) volumetric cardiac images. The goals of this paper are to incorporate the temporal information into LV boundary detection, to link the shape modeling and LV boundary detection together, and to provide a compact representation of recovered LV boundaries to cardiac imaging. The proposed technique introduces spatio-temporal boundary detection and iterative model-based boundary refinement to left ventricular boundary extraction. The proposed technique has been applied to two sets of four-dimensional (4D) computed tomography images. Experimental results are compared with the manually edited images.
Tu
H K
HK
Department of Computer Science and Engineering, University of South Florida, Tampa, USA.
Matheny
A
A
Goldgof
D B
DB
Bunke
H
H
D000465:Algorithms; D000818:Animals; D001145:Arrhythmias, Cardiac / Q000000981:diagnostic imaging / Q000209:etiology; D001281:Atrial Fibrillation / Q000150:complications; D002306:Cardiac Volume; D004285:Dogs; D017143:Fuzzy Logic; D006352:Heart Ventricles / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D007091:Image Processing, Computer-Assisted; D008955:Models, Cardiovascular; D014057:Tomography, X-Ray Computed; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging*; D016277:Ventricular Function, Left