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ABSTRACT: The use of automated methods is becoming increasingly important for assessing cardiac function quantitatively and objectively. In this study, we propose a method for tracking three-dimensional (3-D) left ventricular contours. The method consists of a local optical flow tracker and a global tracker, which uses a statistical model of cardiac motion in an optical-flow formulation. We propose a combination of local and global trackers using gradient-based weights. The algorithm was tested on 35 echocardiographic sequences, with good results (surface error: 1.35 ± 0.46 mm, absolute volume error: 5.4 ± 4.8 mL). This demonstrates the method's potential in automated tracking in clinical quality echocardiograms, facilitating the quantitative and objective assessment of cardiac function.
Ultrasound in medicine & biology 03/2011; 37(4):605-16. · 2.02 Impact Factor
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ABSTRACT: The analysis of echocardiograms, whether visual or automated, is often hampered by ultrasound artifacts which obscure the moving myocardial wall. In this study, a probabilistic framework for tracking the endocardial surface in 3D ultrasound images is proposed, which distinguishes between visible and artifact-obscured myocardium. Motion estimation of visible myocardium relies more on a local, data-driven tracker, whereas tracking of obscured myocardium is assisted by a global, statistical model of cardiac motion. To make this distinction, the expectation-maximization algorithm is applied in a stationary and dynamic frame-of-reference. Evaluation on 35 three-dimensional echocardiographic sequences shows that this artifact-aware tracker gives better results than when no distinction is made. In conclusion, the proposed tracker is able to reduce the influence of artifacts, potentially improving quantitative analysis of clinical quality echocardiograms.
Medical image analysis 12/2010; 14(6):750-8. · 3.09 Impact Factor
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ABSTRACT: Several automated border detection approaches for three-dimensional echocardiography have been developed in recent years, allowing quantification of a range of clinically important parameters. In this review, the background and principles of these approaches and the different classes of methods are described from a practical perspective, as well as the research trends to achieve a robust method.
European Heart Journal – Cardiovascular Imaging 02/2010; 11(2):97-108. · 2.32 Impact Factor
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Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Rotterdam, The Netherlands, 14-17 April, 2010; 01/2010
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Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Rotterdam, The Netherlands, 14-17 April, 2010; 01/2010
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K Y Esther Leung,
Marijn van Stralen,
Attila Nemes,
Marco M Voormolen,
Gerard van Burken,
Marcel L Geleijnse,
Folkert J Ten Cate,
Johan H C Reiber,
Nico de Jong,
Antonius F W van der Steen,
Johan G Bosch
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ABSTRACT: Three-dimensional (3-D) stress echocardiography is a novel technique for diagnosing cardiac dysfunction. It involves evaluating wall motion of the left ventricle, by visually analyzing ultrasound images obtained in rest and in different stages of stress. Since the acquisitions are performed minutes apart, variabilities may exist in the visualized cross-sections. To improve anatomical correspondence between rest and stress, aligning the images is essential. We developed a new intensity-based, sparse registration method to retrieve standard anatomical views from 3-D stress images that were equivalent to the manually selected views in the rest images. Using sparse image planes, the influence of common image artifacts could be reduced. We investigated different similarity measures and different levels of sparsity. The registration was tested using data of 20 patients and quantitatively evaluated based on manually defined anatomical landmarks. Alignment was best using sparse registration with two long-axis and two short-axis views; registration errors were reduced significantly, to the range of interobserver variabilities. In 91% of the cases, the registration result was qualitatively assessed as better than or equal to the manual alignment. In conclusion, sparse registration improves the alignment of rest and stress images, with a performance similar to manual alignment. This is an important step towards objective quantification in 3-D stress echocardiography.
IEEE transactions on medical imaging. 12/2008; 27(11):1568-79.
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K.Y. Esther Leung,
M. van Stralen,
A. Nemes,
M.M. Voormolen,
G. van Burken,
M.L. Geleijnse,
F.J. ten Cate,
J. Reiber,
N. de Jong,
A.F.W. van der Steen,
J.G. Bosch
[show abstract]
[hide abstract]
ABSTRACT: Three-dimensional (3-D) stress echocardiography is a novel technique for diagnosing cardiac dysfunction. It involves evaluating wall motion of the left ventricle, by visually analyzing ultrasound images obtained in rest and in different stages of stress. Since the acquisitions are performed minutes apart, variabilities may exist in the visualized cross-sections. To improve anatomical correspondence between rest and stress, aligning the images is essential. We developed a new intensity-based, sparse registration method to retrieve standard anatomical views from 3-D stress images that were equivalent to the manually selected views in the rest images. Using sparse image planes, the influence of common image artifacts could be reduced. We investigated different similarity measures and different levels of sparsity. The registration was tested using data of 20 patients and quantitatively evaluated based on manually defined anatomical landmarks. Alignment was best using sparse registration with two long-axis and two short-axis views; registration errors were reduced significantly, to the range of interobserver variabilities. In 91% of the cases, the registration result was qualitatively assessed as better than or equal to the manual alignment. In conclusion, sparse registration improves the alignment of rest and stress images, with a performance similar to manual alignment. This is an important step towards objective quantification in 3-D stress echocardiography.
IEEE Transactions on Medical Imaging 12/2008; · 3.64 Impact Factor
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ABSTRACT: Parametric shape representations of endocardial contours, obtained with principal component analysis (PCA) and the orthomax criterion, provide compact descriptors for classifying segmental left ventricular wall motion.
Endocardial contours were delineated in the left ventricular echocardiograms of 129 patients. Parametric models of these shapes were built with PCA and subsequently rotated using the orthomax criterion, producing models with local variations. Shape parameters of this localized model were used to predict the presence of wall motion abnormalities, as determined by expert visual wall motion scoring.
Best results were obtained using the varimax criterion and full variance models. Although traditional PCA models needed 8.0 +/- 3.0 parameters to classify segmental wall motion, only 5.1 +/- 3.2 parameters were needed using the orthomax rotated models (P < .05) to achieve similar classification accuracy. The classification space was also better behaved.
Orthomax rotation generates more local parameters, which are successful in reducing the complexity of wall motion classification. Because pathologies are typically spatially localized, many medical applications involving local classification should benefit from orthomax parameterizations.
Academic radiology 11/2008; 15(11):1416-24. · 2.09 Impact Factor
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K. Y. Esther Leung,
Marijn van Stralen,
Attila Nemes,
Marco M. Voormolen,
Gerard van Burken,
M. L. Geleijnse,
Folkert J. ten Cate,
Johan H. C. Reiber,
Nico de Jong,
Anton F. W. van der Steen,
Johan G. Bosch
IEEE Trans. Med. Imaging. 01/2008; 27:1568-1579.
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ABSTRACT: To quantitatively predict coronary artery diseases, automated analysis may be preferred to current visual assessment of left ventricular (LV) wall motion. In this paper, a novel automated classification method is presented which uses shape models with localized variations. These sparse shape models were built from four-chamber and two-chamber echocardiographic sequences using principal component analysis and orthomax rotations. The resulting shape parameters were then used to classify local wall-motion abnormalities of LV segments. Various orthomax criteria were investigated. In all cases, higher classification correctness was achieved using significantly less shape parameters than before rotation. Since pathologies are typically spatially localized, many medical applications involving local classification should benefit from orthomax parameterizations.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 02/2007; 10(Pt 1):52-9.
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Functional Imaging and Modeling of the Heart, 4th International Conference, FIMH 2007, Salt Lake City, UT, USA, June 7-9, 2007, Proceedings; 01/2007
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ABSTRACT: Rupture of vulnerable plaques in coronary arteries is the major cause of acute coronary syndromes. Most vulnerable plaques consist of a thin fibrous cap covering an atheromous core. These plaques can be identified using intravascular ultrasound (IVUS) palpography, which measures radial strain by cross-correlating RF signals at different intraluminal pressures. Multiple strain images (i.e., partial palpograms) are averaged per heart cycle to produce a more robust compounded palpogram. However, catheter motion due to cardiac activity causes misalignment of the RF signals and thus of the partial palpograms, resulting in less valid strain estimates. To compensate for in-plane catheter rotation and translation, we devised four methods based on block matching. The global rotation block matching (GRBM) and contour mapping (CMAP) methods measure catheter rotation, and local block matching (LBM) and catheter rotation and translation (CRT) estimate displacements of local tissue regions. These methods were applied to nine in vivo pullback acquisitions, made with a 20 MHz phased-array transducer. We found that all these methods significantly increase the number of valid strain estimates in the partial and compounded palpograms (P < 0.008). The best method, LBM, attained an average increase of 17% and 15%, respectively. Implementation of this method should improve the information coming from IVUS palpography, leading to better vulnerable plaque detection.
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control 07/2006; 53(7):1269-80. · 1.69 Impact Factor
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K. Y. Esther Leung,
Marijn van Stralen,
Marco M. Voormolen,
Gerard van Burken,
Attila Nemes,
Folkert J. ten Cate,
Marcel L. Geleijnse,
Nico de Jong,
Antonius F. W. van der Steen,
Johan H. C. Reiber,
Johan G. Bosch
[show abstract]
[hide abstract]
ABSTRACT: Three-dimensional (3D) stress echocardiography is a novel technique for diagnosing cardiac dysfunction, by comparing wall motion of the left ventricle under different stages of stress. For quantitative comparison of this motion, it is essential to register the ultrasound data. We propose an intensity based rigid registration method to retrieve two-dimensional (2D) four-chamber (4C), two-chamber, and short-axis planes from the 3D data set acquired in the stress stage, using manually selected 2D planes in the rest stage as reference. The algorithm uses the Nelder-Mead simplex optimization to find the optimal transformation of one uniform scaling, three rotation, and three translation parameters. We compared registration using the SAD, SSD, and NCC metrics, performed on four resolution levels of a Gaussian pyramid. The registration's effectiveness was assessed by comparing the 3D positions of the registered apex and mitral valve midpoints and 4C direction with the manually selected results. The registration was tested on data from 20 patients. Best results were found using the NCC metric on data downsampled with factor two: mean registration errors were 8.1mm, 5.4mm, and 8.0° in the apex position, mitral valve position, and 4C direction respectively. The errors were close to the interobserver (7.1mm, 3.8mm, 7.4°) and intraobserver variability (5.2mm, 3.3mm, 7.0°), and better than the error before registration (9.4mm, 9.0mm, 9.9°). We demonstrated that the registration algorithm visually and quantitatively improves the alignment of rest and stress data sets, performing similar to manual alignment. This will improve automated analysis in 3D stress echocardiography.© (2006) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
03/2006;
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Medical Imaging and Augmented Reality, MIAR 2006, Third International Workshop, Shanghai, China, August 17-18, 2006, Proceedings; 01/2006
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ABSTRACT: In this paper, we propose a sparse appearance model based registration algorithm for segmenting 3D echocardiograms. The end-diastolic
model is built in 3D sparsely on 2D planes, representing the anatomical 4-chamber, 2-chamber, and short-axis views. Ultrasound
specific intensity normalization and shape-based intensity modeling are employed. The model is matched in an intensity-based
registration approach, by perturbing appearance and pose parameters simultaneously. Leave-one-out experiments on 10 patients
reveal significant improvement in the segmentation using the normalized cross-correlation metric. The registration method
will allow fully automatic extraction of the standard views as used in echocardiography. This will aid in the selection of
images for inter- and intra-patient comparison and may provide an alternative for a complete 3D AAM.
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