Average velocity of ultrasound in the human female breast

Kossoff, G.; Fry, Elizabeth Kelly; Jellins, Jack

doi:10.1121/1.1913526

Cited by 109 publications

(48 citation statements)

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“…Generally, a zone of low velocity (1400-1450 m/s) characterizes subcutaneous fat [33]. The speed in normal dense parenchyma is higher, varying from 1500 m/s to 1550 m/s [30]. In Fig.…”

Section: B Model and Parameters In Numerical Simulationsmentioning

confidence: 99%

“…5(a) and (b) illustrate the acoustic and RF absorption models of the breast, respectively. The acoustic model of the breast in our simulations is based on experimental results on the distribution of acoustic speed in the breast [27]- [30]. Acoustic speed in the breast may vary from 1400 m/s to 1550 m/s.…”

Section: B Model and Parameters In Numerical Simulationsmentioning

confidence: 99%

“…The mean velocity in the subcutaneous zone v f and the breast parenchyma v p are set to be 1437 m/s [27] and 1546 m/s [30], respectively. A random component, which is a normal distribution with a mean of zero and a variance of 33 m/s, is added to the velocity distribution to simulate the velocity fluctuations in the subcutaneous zone [33] and the breast parenchyma [30]. Later, our simulation results show that the random component of velocity will induce little spread in the images due to the cancellation after integration.…”

Section: B Model and Parameters In Numerical Simulationsmentioning

confidence: 99%

“…Using the following parameters, l SB1 < 10 cm (the assumed size of the breast parenchyma), and α = 0.07, in which the mean velocity in the subcutaneous zone v f and the breast parenchyma v p are assumed to be 1437 m/s [28] and 1546 m/s [30], respectively, we have l B1D > 4.9 cm for 1.5 MHz ultrasound and l B1D > 1.63 cm for 0.5 MHz ultrasound. These requirements can be met easily in TAT experiments.…”

Section: Concave Boundarymentioning

confidence: 99%

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Effects of acoustic heterogeneity on the breast thermoacoustic tomography

Wang

2003

SPIE Proceedings

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Abstract-The effects of wavefront distortions induced by acoustic heterogeneities in breast thermoacoustic tomography (TAT) are studied. Amplitude distortions are shown to be insignificant for different scales of acoustic heterogeneities. For wavelength-scale, or smaller, heterogeneities, amplitude distortion of the wavefront is minor as a result of diffraction when the detectors are placed in the far field of the heterogeneities. For larger-scale heterogeneities at the parenchyma wall, by using a ray approach (geometric optics), we show that no refraction-induced multipath interference occurs and, consequently, that no severe amplitude distortion, such as is found in ultrasound tomography, exists. Next, we consider the effects of phase distortions (errors in time-of-flight) in our numerical studies. The numerical results on the spreads of point sources and boundaries caused by the phase distortions are in good agreement with the proposed formula. After that, we demonstrate that the blurring of images can be compensated for by using the distribution of acoustic velocity in the tissues in the reconstructions. The effects of the errors in the acoustical velocities on this compensation also are investigated. An approach to implement the compensation using only TAT data is proposed. Lastly, the differences in the effects of acoustic heterogeneity and the generation of speckles in breast TAT and breast ultrasound imaging are discussed.

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“…Generally, a zone of low velocity (1400-1450 m/s) characterizes subcutaneous fat [33]. The speed in normal dense parenchyma is higher, varying from 1500 m/s to 1550 m/s [30]. In Fig.…”

Section: B Model and Parameters In Numerical Simulationsmentioning

confidence: 99%

Section: B Model and Parameters In Numerical Simulationsmentioning

confidence: 99%

Section: B Model and Parameters In Numerical Simulationsmentioning

confidence: 99%

Section: Concave Boundarymentioning

confidence: 99%

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Effects of acoustic heterogeneity on the breast thermoacoustic tomography

Wang

2003

SPIE Proceedings

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“…encountered in mammography. Our compression model uses the relative ratio of the AT and FGT elastic moduli, which was determined using published values of the ultrasound velocity in different tissue types [19] and relation between the velocity and the elastic modulus [18]. Rectangular slice approximation practically has a shape of a composite 2D elastic beam, positioned between two bars corresponding to the compression plates.…”

Section: Modeling Mammographic Compressionmentioning

confidence: 99%

Mammogram Screening by Automated Followup: A Feasibility Study

Brzakovic¹

1999

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington. VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503. AGENCY USE ONLY (Leave blank)REPORT DATE July 1999 REPORT TYPF ANn DATFS HnVFRFDAnnual ( ABSTRACT (Maximum 200 words)This report describes part of a study aimed at developing a computer-based aid for mammogram screening that makes a detailed comparison between mammograms of the same patient acquired at different screenings and detects changes indicative of cancer. The focus of the work in the past three years has been on putting two mammograms acquired at different time into correspondence. The essence of the approach is identification of control points in two mammograms; these points are used to put regions in two mammograms into correspondence. The emphasis of the work in the past year has been on improving the procedure for determining control points, i.e., points that are the same in two images. For this purpose we have developed a model based approach to identify regions of interest in two mammograms. The model encompasses breast tissue characteristics, modeling of compression effects and formation of Xray images. The model is utilized to develop appropriate segmentation operators and the report discusses utilization of the model to detect lobules and ducts. The model can also be utilized for generating synthetic mammograms.Presently, we are evaluating the improvements this approach offers, relative to our original approach, in terms of determining more reliably control points, namely branching points of ducts.

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Speed of Sound

Bamber

2004

Physical Principles of Medical Ultrasonics

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Average velocity of ultrasound in the human female breast

Cited by 109 publications

References 0 publications

Effects of acoustic heterogeneity on the breast thermoacoustic tomography

Effects of acoustic heterogeneity on the breast thermoacoustic tomography

Mammogram Screening by Automated Followup: A Feasibility Study

Speed of Sound

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