Generalized gradient vector flow external forces for active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Image processing and analysis in tagged cardiac MRI
Handbook of medical imaging
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Tag Separation in Cardiac Tagged MRI
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Tagged MRI-based studies of cardiac function
FIMH'03 Proceedings of the 2nd international conference on Functional imaging and modeling of the heart
Segmentation of 4D cardiac MRI: Automated method based on spatio-temporal watershed cuts
Image and Vision Computing
Boosting and nonparametric based tracking of tagged MRI cardiac boundaries
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Automated detection of left ventricle in 4d MR images: experience from a large study
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
A learning framework for the automatic and accurate segmentation of cardiac tagged MRI images
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
Fast segmentation of the mitral valve leaflet in echocardiography
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Scaffolding-based segmentation of coronary vascular structures
VG'05 Proceedings of the Fourth Eurographics / IEEE VGTC conference on Volume Graphics
Computer Vision and Image Understanding
| Hi-index | 0.00 |
In this paper we describe a completely automated volume-based method for the segmentation of the left and right ventricles in 4D tagged MR (SPAMM) images for quantitative cardiac analysis. We correct the background intensity variation in each volume caused by surface coils using a new scale-based fuzzy connectedness procedure. We apply 3D grayscale opening to the corrected data to create volumes containing only the blood filled regions. We threshold the volumes by minimizing region variance or by an adaptive statistical thresholding method. We isolate the ventricular blood filled regions using a novel approach based on spatial and temporal shape similarity. We use these regions to define the endocardium contours and use them to initialize an active contour that locates the epicardium through the gradient vector flow of an edgemap of a grayscale-closed image. Both quantitative and qualitative results on normal and diseased patients are presented.