Realistic Simulation of B-Scan Images

Seggie, D.A.; Leeman, S.; Burge, R. E.

doi:10.1109/ultsym.1983.198151

Cited by 7 publications

(4 citation statements)

References 4 publications

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“…The FE displacement solution was applied in a series of simulated ultrasound radio-frequency (RF) signals in MATLAB 2008b (Mathworks, Natic, MA, U.S.A.) generated using a 2D linear convolutional scattering model (Bamber and Dickinson 1980, Seggie et al 1983). The simulated linear array had 128 elements, center frequency of 7.5 MHz, beamwidth of 1 mm, 60% bandwidth with a sampling frequency of 80 MHz.…”

Section: Methodsmentioning

confidence: 99%

Performance Assessment of HIFU Lesion Detection by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): A 3-D Finite-Element-Based Framework with Experimental Validation

Hou

Luo

Marquet

et al. 2011

Ultrasound in Medicine & Biology

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Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a novel high-intensity focused ultrasound (HIFU) therapy monitoring method with feasibilities demonstrated in vitro, ex vivo and in vivo. Its principle is based on Amplitude-modulated (AM) - Harmonic Motion Imaging (HMI), an oscillatory radiation force used for imaging the tissue mechanical response during thermal ablation. In this study, a theoretical framework of HMIFU is presented, comprising a customized nonlinear wave propagation model, a finite-element (FE) analysis module, and an image-formation model. The objective of this study is to develop such a framework in order to 1) assess the fundamental performance of HMIFU in detecting HIFU lesions based on the change in tissue apparent elasticity, i.e., the increasing Young's modulus, and the HIFU lesion size with respect to the HIFU exposure time and 2) validate the simulation findings ex vivo. The same HMI and HMIFU parameters as in the experimental studies were used, i.e., 4.5-MHz HIFU frequency and 25 Hz AM frequency. For a lesion-to-background Young's modulus ratio of 3, 6, and 9, the FE and estimated HMI displacement ratios were equal to 1.83, 3.69, 5.39 and 1.65, 3.19, 4.59, respectively. In experiments, the HMI displacement followed a similar increasing trend of 1.19, 1.28, and 1.78 at 10-s, 20-s, and 30-s HIFU exposure, respectively. In addition, moderate agreement in lesion size growth was also found in both simulations (16.2, 73.1 and 334.7 mm2) and experiments (26.2, 94.2 and 206.2 mm2). Therefore, the feasibility of HMIFU for HIFU lesion detection based on the underlying tissue elasticity changes was verified through the developed theoretical framework, i.e., validation of the fundamental performance of the HMIFU system for lesion detection, localization and quantification, was demonstrated both theoretically and ex vivo.

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Section: Methodsmentioning

confidence: 99%

Performance Assessment of HIFU Lesion Detection by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): A 3-D Finite-Element-Based Framework with Experimental Validation

Hou

Luo

Marquet

et al. 2011

Ultrasound in Medicine & Biology

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“…The rf sig nals were sim u lated in Matlab 7.2 (Mathworks, Natick, MA, USA) us ing a lin ear convolutional scat ter ing model. 55,56 The scat terer was ran domly dis trib uted. The lin ear ar ray had 64 el e ments, a cen ter fre quency of 7.5 MHz, a frame rate of 124 frames/s, a beam width of 2 mm and 60% band width.…”

Section: Im Age For Ma Tionmentioning

confidence: 99%

Simulation Study of Amplitude-Modulated (AM) Harmonic Motion Imaging (HMI) for Stiffness Contrast Quantification with Experimental Validation

et al. 2010

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The objective of this study is to show that Harmonic Motion Imaging (HMI) can be used as a reliable tumor-mapping technique based on the tumor's distinct stiffness at the early onset of disease. HMI is a radiation-force-based imaging method that generates a localized vibration deep inside the tissue to estimate the relative tissue stiffness based on the resulting displacement amplitude. In this paper, a finite-element model (FEM) study is presented, followed by an experimental validation in tissue-mimicking polyacrylamide gels and excised human breast tumors ex vivo. This study compares the resulting tissue motion in simulations and experiments at four different gel stiffnesses and three distinct spherical inclusion diameters. The elastic moduli of the gels were separately measured using mechanical testing. Identical transducer parameters were used in both the FEM and experimental studies, i.e., a 4.5-MHz single-element focused ultrasound (FUS) and a 7.5-MHz diagnostic (pulse-echo) transducer. In the simulation, an acoustic pressure field was used as the input stimulus to generate a localized vibration inside the target. Radiofrequency (rf) signals were then simulated using a 2D convolution model. A one-dimensional cross-correlation technique was performed on the simulated and experimental rf signals to estimate the axial displacement resulting from the harmonic radiation force. In order to measure the reliability of the displacement profiles in estimating the tissue stiffness distribution, the contrast-transfer efficiency (CTE) was calculated. For tumor mapping ex vivo, a harmonic radiation force was applied using a 2D raster-scan technique. The 2D HMI images of the breast tumor ex vivo could detect a malignant tumor (20 x 10 mm2) surrounded by glandular and fat tissues. The FEM and experimental results from both gels and breast tumors ex vivo demonstrated that HMI was capable of detecting and mapping the tumor or stiff inclusion with various diameters or stiffnesses. HMI may thus constitute a promising technique in tumor detection (>3 mm in diameter) and mapping based on its distinct stiffness.

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“…The acoustic intensity was normalized and scaled to a peak in situ, the peak average intensity value was 236 W/cm 2 at a focal depth of 20 mm. The image formation model was simulated in Matlab 7.2 (Mathworks, Natick, MA, USA) using a 2D convolutional image formation model [13,14] with 128 acoustic elements, a center frequency of 7.5 MHz and a 40 MHz sampling frequency. Only the displacement estimation on the center RF line was considered in the validation with the single-element pulse-echo transducer used in experiments.…”

Section: Finite-element Modelmentioning

confidence: 99%

9C-5 2D Simulation of the Harmonic Motion Imaging (HMI) with Experimental Validation

Maleke

Luo

Konofagou

2007

2007 IEEE Ultrasonics Symposium Proceedings

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Amplitude-modulated (AM) harmonic motion imaging (HMI) is one of the radiation-force-based techniques, which has the capability of imaging tissue mechanical properties during the application of the acoustic radiation force. Since only displacement images have been presented until now, the theory between tissue displacement and modulus in AM-HMI has not been validated. Here, a finiteelement model (FEM) is used to accurately model the dynamic response in tissue mimicking phantoms to evaluate HMI performance. The FEM and experimental results of phantoms with the same stiffness variations are compared and used to describe the behavior of tissue during the application of the stimulus. A harmonic force was generated by a 4.68 MHz single-element focused ultrasound (FUS) transducer. Since the focus is highly localized and has a harmonic response from AM beam, the motion characteristics can be directly related to the regional tissue modulus. The resulting motion was imaged simultaneously using a diagnostic (pulse-echo) transducer at center frequency of 7.5 MHz. RF signals were acquired using a standard pulse-echo technique with a PRF of 5.4 kHz. 1D cross-correlation technique was performed to estimate the resulting axial displacement. In the FEM simulation, a rectangular mesh with dimensions of 35 mm in the axial and 30 mm in the lateral directions was generated. There were a total of 2771 nodes and 5424 triangular elements in the mesh. For simplicity, the mesh was assumed to be a purely elastic medium with Young's modulus of 10 kPa. The acoustic pressure field was simulated in Field II using the same transducer parameters as in the experiment. This pressure field was used as the excitation force to generate displacements. The imaging field was simulated in Matlab 7.2 using a 2D convolutional image formation model with 128 acoustic elements, a center frequency of 7.5 MHz and 40 MHz sampling frequency. Only the displacement estimation at the center RF lines was considered in the validation with the single-element pulse-echo transducer used in the experiments. A good agreement between the results from the FEM and experiment findings was observed in phantom study. Finally, in vivo application is presented.

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Realistic Simulation of B-Scan Images

Cited by 7 publications

References 4 publications

Performance Assessment of HIFU Lesion Detection by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): A 3-D Finite-Element-Based Framework with Experimental Validation

Performance Assessment of HIFU Lesion Detection by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): A 3-D Finite-Element-Based Framework with Experimental Validation

Simulation Study of Amplitude-Modulated (AM) Harmonic Motion Imaging (HMI) for Stiffness Contrast Quantification with Experimental Validation

9C-5 2D Simulation of the Harmonic Motion Imaging (HMI) with Experimental Validation

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