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1.
J Acoust Soc Am ; 130(5): 3148-57, 2011 Nov.
Article in English | MEDLINE | ID: mdl-22087943

ABSTRACT

In medical ultrasound, fundamental imaging (FI) uses the reflected echoes from the same spectral band as that of the emitted pulse. The transmission frequency determines the trade-off between penetration depth and spatial resolution. Tissue harmonic imaging (THI) employs the second harmonic of the emitted frequency band to construct images. Recently, superharmonic imaging (SHI) has been introduced, which uses the third to the fifth (super) harmonics. The harmonic level is determined by two competing phenomena: nonlinear propagation and frequency dependent attenuation. Thus, the transmission frequency yielding the optimal trade-off between the spatial resolution and the penetration depth differs for THI and SHI. This paper quantitatively compares the concepts of fundamental, second harmonic, and superharmonic echocardiography at their optimal transmission frequencies. Forward propagation is modeled using a 3D-KZK implementation and the iterative nonlinear contrast source (INCS) method. Backpropagation is assumed to be linear. Results show that the fundamental lateral beamwidth is the narrowest at focus, while the superharmonic one is narrower outside the focus. The lateral superharmonic roll-off exceeds the fundamental and second harmonic roll-off. Also, the axial resolution of SHI exceeds that of FI and THI. The far-field pulse-echo superharmonic pressure is lower than that of the fundamental and second harmonic. SHI appears suited for echocardiography and is expected to improve its image quality at the cost of a slight reduction in depth-of-field.


Subject(s)
Computer Simulation , Echocardiography , Image Enhancement , Models, Theoretical , Ultrasonics/methods , Fourier Analysis , Nonlinear Dynamics , Numerical Analysis, Computer-Assisted , Pressure , Scattering, Radiation , Time Factors
2.
Article in English | MEDLINE | ID: mdl-22083765

ABSTRACT

Tissue second-harmonic imaging is currently the default mode in commercial diagnostic ultrasound systems. A new modality, superharmonic imaging (SHI), combines the third through fifth harmonics originating from nonlinear wave propagation through tissue. SHI could further improve the resolution and quality of echographic images. The superharmonics have gaps between the harmonics because the transducer has a limited bandwidth of about 70% to 80%. This causes ghost reflection artifacts in the superharmonic echo image. In this work, a new dual-pulse frequency compounding (DPFC) method to eliminate these artifacts is introduced. In the DPFC SHI method, each trace is constructed by summing two firings with slightly different center frequencies. The feasibility of the method was established using a single-element transducer. Its acoustic field was modeled in KZK simulations and compared with the corresponding measurements obtained with a hydrophone apparatus. Subsequently, the method was implemented on and optimized for a setup consisting of an interleaved phased-array transducer (44 elements at 1 MHz and 44 elements at 3.7 MHz, optimized for echocardiography) and a programmable ultrasound system. DPFC SHI effectively suppresses the ghost reflection artifacts associated with imaging using multiple harmonics. Moreover, compared with the single-pulse third harmonic, DPFC SHI improved the axial resolution by 3.1 and 1.6 times at the -6-dB and -20-dB levels, respectively. Hence, DPFC offers the possibility of generating harmonic images of a higher quality at a cost of a moderate frame rate reduction.


Subject(s)
Algorithms , Elasticity Imaging Techniques/methods , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Signal Processing, Computer-Assisted , Elasticity Imaging Techniques/instrumentation , Phantoms, Imaging , Reproducibility of Results , Sensitivity and Specificity
3.
Ultrasound Med Biol ; 37(4): 605-16, 2011 Apr.
Article in English | MEDLINE | ID: mdl-21376448

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.


Subject(s)
Echocardiography/methods , Heart Ventricles/diagnostic imaging , Image Interpretation, Computer-Assisted/methods , Models, Cardiovascular , Movement/physiology , Pattern Recognition, Automated/methods , Ventricular Function, Left/physiology , Algorithms , Computer Simulation , Humans , Image Enhancement/methods , Motion , Reproducibility of Results , Sensitivity and Specificity
4.
Med Image Anal ; 14(6): 750-8, 2010 Dec.
Article in English | MEDLINE | ID: mdl-20584623

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.


Subject(s)
Algorithms , Artifacts , Coronary Artery Disease/diagnostic imaging , Echocardiography, Three-Dimensional/methods , Image Interpretation, Computer-Assisted/methods , Pattern Recognition, Automated/methods , Data Interpretation, Statistical , Humans , Image Enhancement/methods , Reproducibility of Results , Sensitivity and Specificity
5.
Article in English | MEDLINE | ID: mdl-20178912

ABSTRACT

For several years, the standard in ultrasound imaging has been second-harmonic imaging. A new imaging technique dubbed "super-harmonic imaging" (SHI) was recently proposed. It takes advantage of the higher - third to fifth - harmonics arising from nonlinear propagation or ultrasound-contrast-agent (UCA) response. Next to its better suppression of near-field artifacts, tissue SHI is expected to improve axial and lateral resolutions resulting in clearer images than second-harmonic imaging. When SHI is used in combination with UCAs, a better contrast-to-tissue ratio can be obtained. The use of SHI implies a large dynamic range and requires a sufficiently sensitive array over a frequency range from the transmission frequency up to its fifth harmonic (bandwidth > 130%). In this paper, we present the characteristics and performance of a new interleaved dual frequency array built chiefly for SHI. We report the rationale behind the design choice, frequencies, aperture, and piezomaterials used. The array is efficient both in transmission and reception with well-behaved transfer functions and a combined -6-dB bandwidth of 144%. In addition, there is virtually no contamination of the harmonic components by spurious transducer transmission, due to low element-to-element crosstalk (< 30 dB) and a low transmission efficiency of the odd harmonics (< 46 dB). The interleaved array presented in this article possesses ideal characteristics for SHI and is suitable for other methods like second-harmonic, subharmonic, and second-order ultrasound field (SURF) imaging.


Subject(s)
Echocardiography, Doppler/instrumentation , Echocardiography, Doppler/methods , Transducers , Computer Simulation , Contrast Media , Nonlinear Dynamics , Normal Distribution
6.
Article in English | MEDLINE | ID: mdl-20040400

ABSTRACT

This study proposes a novel algorithm for luminal strain reconstruction from sparse irregularly sampled strain measurements. It is based on the normalized convolution (NC) algorithm. The novel extension comprises the multilevel scheme, which takes into account the variable sampling density of the available strain measurements during the cardiac cycle. The proposed algorithm was applied to restore luminal strain values in intravascular ultrasound (IVUS) palpography. The procedure of reconstructing and averaging the strain values acquired during one cardiac cycle forms a technique, coined as reconstructive compounding. The accuracy of strain reconstruction was initially tested on the luminal strain map, computed from 3 in vivo IVUS pullbacks. The high quality of strain restoration was observed after systematically removing up to 90% of the initial elastographic measurements. The restored distributions accurately reproduced the original strain patterns and the error did not exceed 5%. The experimental validation of the reconstructed compounding technique was performed on 8 in vivo IVUS pullbacks. It demonstrated that the relative decrease in number of invalid strain estimates amounts to 92.05 +/- 6.03% and 99.17 +/- 0.92% for the traditional and reconstructive strain compounding schemes, respectively. In conclusion, implementation of the reconstructive compounding scheme boosts the diagnostic value of IVUS palpography.


Subject(s)
Algorithms , Blood Vessels/diagnostic imaging , Blood Vessels/physiology , Elasticity Imaging Techniques/methods , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Animals , Elastic Modulus/physiology , Humans , Reproducibility of Results , Sensitivity and Specificity
7.
Article in English | MEDLINE | ID: mdl-19049919

ABSTRACT

Intravascular ultrasound (IVUS) strain imaging of the luminal layer in coronary arteries, coined as IVUS palpography, utilizes conventional radio frequency (RF) signals acquired at 2 different levels of a compressional load. The signals are cross-correlated to obtain the microscopic tissue displacements, which can be directly translated into local strain of the vessel wall. However, (apparent) tissue motion and nonuniform deformation of the vessel wall, due to catheter wiggling, reduce signal correlation and result in invalid strain estimates. Implications of probe motion were studied on the tissue-mimicking phantom. The measured circumferential tissue displacement and level of the speckle decorrelation amounted to 12 degrees and 0.58, respectively, for the catheter displacement of 456 microm. To compensate for the motion artifacts in IVUS palpography, a novel method based on the feature-based scale-space optical flow (OF), and classical block matching (BM) algorithm, were employed. The computed OF vector and BM displacement fields quantify the amount of local tissue misalignment in consecutive frames. Subsequently, the extracted circumferential displacements are used to realign the signals before strain computation. Motion compensation reduces the RF signal decorrelation and increases the number of valid strain estimates. The advantage of applying the motion correction in IVUS palpography was demonstrated in a midscale validation study on 14 in vivo pullbacks. Both methods substantially increase the number of valid strain estimates in the partial and compounded palpograms. Mean relative improvement in the number of valid strain estimates with motion compensation in comparison to one without motion compensation amounts to 28% and 14%, respectively. Implementation of motion compensation methods boosts the diagnostic value of IVUS palpography.


Subject(s)
Algorithms , Artifacts , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Ultrasonography, Interventional/methods , Humans , Motion , Phantoms, Imaging , Reproducibility of Results , Sensitivity and Specificity , Ultrasonography, Interventional/instrumentation
8.
IEEE Trans Inf Technol Biomed ; 12(5): 595-605, 2008 Sep.
Article in English | MEDLINE | ID: mdl-18779074

ABSTRACT

Manual quantitative analysis of cardiac left ventricular function using Multislice CT and MR is arduous because of the large data volume. In this paper, we present a 3-D active shape model (ASM) for semiautomatic segmentation of cardiac CT and MR volumes, without the requirement of retraining the underlying statistical shape model. A fuzzy c-means based fuzzy inference system was incorporated into the model. Thus, relative gray-level differences instead of absolute gray values were used for classification of 3-D regions of interest (ROIs), removing the necessity of training different models for different modalities/acquisition protocols. The 3-D ASM was evaluated using 25 CT and 15 MR datasets. Automatically generated contours were compared to expert contours in 100 locations. For CT, 82.4% of epicardial contours and 74.1% of endocardial contours had a maximum error of 5 mm along 95% of the contour arc length. For MR, those numbers were 93.2% (epicardium) and 91.4% (endocardium). Volume regression analysis revealed good linear correlations between manual and semiautomatic volumes, r(2) >/= 0.98. This study shows that the fuzzy inference 3-D ASM is a robust promising instrument for semiautomatic cardiac left ventricle segmentation. Without retraining its statistical shape component, it is applicable to routinely acquired CT and MR studies.


Subject(s)
Fuzzy Logic , Heart Ventricles/diagnostic imaging , Heart Ventricles/pathology , Image Interpretation, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Tomography, X-Ray Computed/methods , Ventricular Dysfunction, Left/diagnosis , Algorithms , Computer Simulation , Humans , Models, Cardiovascular , Pattern Recognition, Automated/methods
9.
IEEE Trans Inf Technol Biomed ; 12(3): 277-89, 2008 May.
Article in English | MEDLINE | ID: mdl-18693495

ABSTRACT

The rupture of thin-cap fibroatheroma (TCFA) plaques is a major cause of acute coronary events. A TCFA has a trombogenic soft lipid core, shielded from the blood stream by a thin, possibly inflamed, stiff cap. The majority of atherosclerotic plaques resemble a TCFA in terms of overall structural composition, but have a more complex, heterogeneous morphology. An assessment of the material distribution is vital for quantifying the plaque's mechanical stability and for determining the effect of plaque-stabilizing pharmaceutical agents. We describe a new automated inverse elasticity method, intravascular ultrasound (IVUS) modulography, which is capable of reconstructing a heterogeneous Young's modulus distribution. The elastogram (i.e., spatial strain distribution) of the plaque is the input for the method, and is measured using the clinically available technique, IVUS elastography. Our method incorporates a novel divide-and-conquer strategy, allowing the reconstruction of TCFAs as well as heterogeneous plaques with localized regions of soft, weakened tissue. The method was applied to ex vivo elastograms, which were simulated from the cross sections of postmortem human coronary plaques. To demonstrate the clinical feasibility of the method, measured elastograms from human atherosclerotic coronary arteries were analyzed. One elastogram was measured in vitro; the other, in vivo. The method approximated the true Young's modulus distribution of all simulated plaques, while the in vitro reconstruction was in agreement with histology. In conclusion, the IVUS modulography in combination with the IVUS elastography has strong potential to become an all-encompassing modality for detecting plaques, for assessing the information related to their rupture-proneness, and for imaging their heterogeneous elastic material composition.


Subject(s)
Algorithms , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/physiopathology , Elasticity Imaging Techniques/methods , Image Interpretation, Computer-Assisted/methods , Models, Cardiovascular , Ultrasonography, Interventional/methods , Computer Simulation , Elasticity , Humans , Image Enhancement/methods , Reproducibility of Results , Sensitivity and Specificity , Stress, Mechanical
10.
IEEE Trans Inf Technol Biomed ; 12(3): 356-65, 2008 May.
Article in English | MEDLINE | ID: mdl-18693503

ABSTRACT

The quantitative assessment of and compensation for catheter rotation in intravascular ultrasound images presents a fundamental problem for noninvasive characterization of the mechanical properties of the coronary arteries. A method based on the scale-space optical flow algorithm with a feature-based weighting scheme is proposed to account for the aforementioned artifact. The computed vector field, describing the misalignment between two consecutive frames, allows the quantitative assessment of the amount of vessel wall tissue motion, which is directly related to the catheter rotation. Algorithm accuracy and robustness were demonstrated on two tissue-mimicking phantoms, subjected to controlled amount of angular deviation. The proposed method shows a great reliability in the prediction of catheter rotational motion up to 4 degrees.


Subject(s)
Catheterization/methods , Coronary Vessels/diagnostic imaging , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Pattern Recognition, Automated/methods , Ultrasonography, Interventional/methods , Algorithms , Artificial Intelligence , Humans , Phantoms, Imaging , Reproducibility of Results , Rheology/methods , Rotation , Sensitivity and Specificity , Ultrasonography, Interventional/instrumentation
12.
Med Image Anal ; 10(2): 286-303, 2006 Apr.
Article in English | MEDLINE | ID: mdl-16439182

ABSTRACT

A new technique (SPASM) based on a 3D-ASM is presented for automatic segmentation of cardiac MRI image data sets consisting of multiple planes with arbitrary orientations, and with large undersampled regions. Model landmark positions are updated in a two-stage iterative process. First, landmark positions close to intersections with images are updated. Second, the update information is propagated to the regions without image information, such that new locations for the whole set of the model landmarks are obtained. Feature point detection is performed by a fuzzy inference system, based on fuzzy C-means clustering. Model parameters were optimized on a computer cluster and the computational load distributed by grid computing. SPASM was applied to image data sets with an increasing sparsity (from 2 to 11 slices) comprising images with different orientations and stemming from different MRI acquisition protocols. Segmentation outcomes and calculated volumes were compared to manual segmentation on a dense short-axis data configuration in a 3D manner. For all data configurations, (sub-)pixel accuracy was achieved. Performance differences between data configurations were significantly different (p<0.05) for SA data sets with less than 6 slices, but not clinically relevant (volume differences<4 ml). Comparison to results from other 3D model-based methods showed that SPASM performs comparable to or better than these other methods, but SPASM uses considerably less image data. Sensitivity to initial model placement proved to be limited within a range of position perturbations of approximately 20 mm in all directions.


Subject(s)
Algorithms , Artificial Intelligence , Heart/anatomy & histology , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Pattern Recognition, Automated/methods , Humans , Reproducibility of Results , Sensitivity and Specificity , Software
13.
J Magn Reson Imaging ; 22(6): 754-64, 2005 Dec.
Article in English | MEDLINE | ID: mdl-16270293

ABSTRACT

PURPOSE: To theoretically and experimentally investigate the influence of the automated cardiovascular magnetic resonance (CMR) scan planning pitfalls, namely inaccurate positioning and tilting of short-axis (SA) imaging planes, on quantification of the left ventricular (LV) dimensions and function. MATERIALS AND METHODS: Eleven healthy subjects and eight patients underwent CMR. Manually and automatically planned SA sets were acquired. To obtain the quantitative measurements of LV function, one observer performed image analysis twice. The agreement between planning methods, as well as the decomposition of the total variation into interstudy and intraobserver components was measured. RESULTS: The decomposition of the total variation showed that the interstudy factor accounts for 70-85% of the total variation, while the rest is due to the intraobserver factor. Moreover, the relative contribution of the interstudy factor remains independent from errors in slice positioning and small angular deviation of SA stacks from the optimal orientation. Good agreement between the theoretical and measured variability factors was observed. CONCLUSION: Global LV function derived from the automatically planned CMR acquisitions yield accurate quantification of the human cardiovascular system. Inaccurate positioning and tilting of SA images does not affect the quantitative measurements of LV function. The computer-aided system for automated CMR has proven clinical applicability.


Subject(s)
Heart Ventricles/anatomy & histology , Magnetic Resonance Imaging/methods , Ventricular Function, Left/physiology , Adult , Aged , Female , Humans , Male , Middle Aged , Observer Variation
14.
J Cardiovasc Magn Reson ; 7(2): 447-57, 2005.
Article in English | MEDLINE | ID: mdl-15881528

ABSTRACT

PURPOSE: To assess the intra- and inter-operator variability of the manual planning of cardiovascular magnetic resonance imaging and to evaluate the influence of these factors on the functional parameters of the left ventricle (LV). METHOD: The study population consisted of 10 healthy volunteers. For each subject the manual planning of the short-axis cine acquisitions was carried out twice by one operator and once by a second operator. Left ventricular volume, mass, and function were manually evaluated twice by one experienced observer, resulting in an approximation of the intra-observer variability factor. The intra- and inter-operator variation factors were estimated as the difference between the total and intra-observer variation components. RESULTS: LV end-diastolic volume varied by 3.3% and 4.16%, and LV end-systolic volume by 5.84% and 6.23% for intra- and inter-operator studies, respectively. The variability for LV mass at end-diastole was equal to 4.23% in both studies. For the ejection fraction the variability was 3.56% and 2.97% for intra- and inter-operator studies, respectively. Comparison of reproducibility between intra- and inter-operator studies resulted in insignificant statistical differences. Bland-Altman limits of agreements revealed no systematic bias in differences between measurements with respect to their means. Reliability of the planning expressed as the angular deviation of the short-axis imaging planes amounts to 2.67 -/+ 1.5 degrees and 4.99 +/- 2.17 degrees for the intra-operator and inter-operator studies, respectively. For EDV, ESV, and EF approximately 75-80% of the total variation can be explained by the within or between operator variation, while the same percentage is 60% for LVM. CONCLUSIONS: Our study confirms the excellent inter- and intra-operator reproducibility of the cardiovascular magnetic resonance measurements of the left ventricular volumes and mass in a group of healthy volunteers.


Subject(s)
Heart Ventricles/pathology , Magnetic Resonance Imaging, Cine , Ventricular Function, Left/physiology , Adult , Diastole/physiology , Female , Humans , Image Processing, Computer-Assisted , Male , Reproducibility of Results , Stroke Volume/physiology , Systole/physiology
15.
Article in English | MEDLINE | ID: mdl-16686052

ABSTRACT

This paper presents a new approach for lung registration and cardiac motion prediction, based on a 3D geometric model of the left lung. Feature points, describing a shape of this anatomical object, are automatically extracted from acquired tomographic images. The "goodness-of-fit" measure is assessed at each step in the iterative scheme until spatial alignment between the model and subject's specific data is achieved. We applied the proposed methods to register the 3D lung surfaces of 5 healthy volunteers of thoracic MRI acquired in different respiratory phases. We also utilized this approach to predict the spatial displacement of the human heart due to respiration. The obtained results demonstrate a promising registration performance.


Subject(s)
Heart/anatomy & histology , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Lung/anatomy & histology , Magnetic Resonance Imaging/methods , Movement , Subtraction Technique , Algorithms , Image Enhancement/methods , Reproducibility of Results , Sensitivity and Specificity
16.
Invest Radiol ; 39(12): 747-55, 2004 Dec.
Article in English | MEDLINE | ID: mdl-15550836

ABSTRACT

RATIONALE AND OBJECTIVE: This study investigates the use of an automated observer-independent planning system for short-axis cardiovascular magnetic resonance (MR) acquisitions in the clinical environment. The capacity of the automated method to produce accurate measurements of left ventricular dimensions and function was quantitatively assessed in normal subjects and patients. METHODS: Fourteen healthy volunteers and 8 patients underwent cardiovascular MR (CMR) acquisitions for ventricular function assessment. Short-axis datasets of the left ventricle (LV) were acquired in 2 ways: manually planned and generated in an automatic fashion. End-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), and left ventricular mass (LVM) were derived from the 2 datasets. The agreement between the manual and automatic planning methods was assessed. RESULTS: The mean differences between the manual and automated CMR planning methods for the normal subjects and patients were 5.89 mL and 1.93 mL (EDV), 1.14 mL and -0.41 mL (ESV), 0.81% and 0.89% (EF), and 4.35 g and 3.88 g (LVM), respectively. There was no significant difference in ESV and EF. LVM significantly differed in both groups, whereas EDV was significantly different in the normal subjects and insignificantly different in the patients. The variability coefficients were 2.8 and 3.59 (EDV), 3.3 and 5.03 (ESV), 1.79 and 2.65 (EF), and 4.36 and 2.27 (LVM) for the normal subjects and patients, respectively. The mean angular deviation of the LV axes turned out to be 8.58 +/- 5.76 degrees for the normal subjects and 8.35 +/- 5.15 degrees for the patients. CONCLUSIONS: Automated CMR planning method can provide accurate measurements of LV dimensions in normal subjects and patients, and therefore, can be used in the clinical environment for functional assessment of the human cardiovascular system.


Subject(s)
Heart Ventricles/anatomy & histology , Magnetic Resonance Imaging/methods , Mitral Valve Insufficiency/pathology , Myocardial Ischemia/pathology , Adult , Female , Heart Ventricles/pathology , Humans , Male , Prospective Studies , Reference Values , Reproducibility of Results
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