Elastography: A systems approach

Ophir, Jonathan; Kallel, F.; Varghese, Tomy; Bertrand, Michel; Céspedes, I.; Ponnekanti, H.

doi:10.1002/(sici)1098-1098(1997)8:1<89::aid-ima11>3.0.co;2-g

Cited by 73 publications

(31 citation statements)

References 8 publications

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“…After their first publication in 1991 (Ophir et al), Kallel and Bertrand (1996) and Ophir et al (1997) published a series of papers describing an iterative solution of the IEP. The method reported treated the IEP as an optimisation problem which is solved with a NewtonRaphson method.…”

Section: Iterative Approachesmentioning

confidence: 99%

Algorithms for ultrasound elastography: a survey

Sette

Goethals

D'hooge

et al. 2011

Computer Methods in Biomechanics and Biomedical Engineering

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Elastography is a useful and interesting technique that can be used to infer stiffness information from ultrasound medical images. In one decade of activity, the scientific community has developed this technique to a more and more mature stage, such that it has evolved into a fruitful application for clinical practice. During this decade, the evolution has proceeded from qualitative stiffness information to numerical quantification using different algorithms and approaches, based on both iterative and direct approaches. Moreover, different post- and pre-processing techniques as well as evaluation methods have been implemented. This work presents a survey on the methods developed by giving a short overview of algorithms and mathematical solutions and by analysing results and comparing methodologies.

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Section: Iterative Approachesmentioning

confidence: 99%

Algorithms for ultrasound elastography: a survey

Sette

Goethals

D'hooge

et al. 2011

Computer Methods in Biomechanics and Biomedical Engineering

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“…As a result, the goal of elastography will be the calculation of distribution throughout the tissue which is governed by (1)-(3). This is an inverse problem which can be solved using direct [7], [10] or iterative [8], [9], [11] techniques. One component of an iterative inversion algorithm is the forward model.…”

Section: Theorymentioning

confidence: 99%

“…The second step of the iteration is to update the modulus estimate using the measured displacement vector . Unlike other investigators [8], [9], [11] who use costly and noise-sensitive nonlinear least squares algorithms, we update the modulus using (3). From this matrix equation, it can be seen that the elasticity modulus can be computed from any one strain component and the three normal stress components.…”

Section: Theorymentioning

confidence: 99%

“…This means that the reconstructed modulus at each iteration is not only degraded by the noisy measured strain but also degraded by the low quality modulus , which was reconstructed in the previous iteration. However, due to the use of the geometrical constraint to enforce a discrete modulus distribution at each step of the iteration and ignoring the variation of within the tissue, the variance of the modulus estimate at any iteration step is related to the measured strain component and its variance by (9) where is the number of elements contained in the tumor ROI and angle brackets represent mean value. In terms of strain and reconstructed modulus signal-to-noise ratio (SNR) ( and ), we have (10) The normal tissue volumes also contribute noise to the modulus estimate, but the effect is usually negligible since many more FEs are involved in the averaging compared to tumor.…”

Section: Theorymentioning

confidence: 99%

“…Many investigators have attempted to solve the elastography problem while assuming fully heterogeneous tissue. Among these investigators, Skovoroda et al [7], Kallel and Bertrand [8], Ophir et al [9], Chenevert et al [4] and, more recently, Bishop et al [10] and Doyley et al [11] have used the quasi-static technique. Also, Manduca et al [12] have used harmonic shear actuation while more recently van Houten et al [13] and Sinkus et al [6] have used harmonic compressional actuation for tissue stimulation.…”

Section: Introductionmentioning

confidence: 99%

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A constrained modulus reconstruction technique for breast cancer assessment

Samani

Bishop

Plewes

2001

IEEE Trans. Med. Imaging

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A reconstruction technique for breast tissue elasticity modulus is described. This technique assumes that the geometry of normal and suspicious tissues is available from a contrast-enhanced magnetic resonance image. Furthermore, it is assumed that the modulus is constant throughout each tissue volume. The technique, which uses quasi-static strain data, is iterative where each iteration involves modulus updating followed by stress calculation. Breast mechanical stimulation is assumed to be done by two compressional rigid plates. As a result, stress is calculated using the finite element method based on the well-controlled boundary conditions of the compression plates. Using the calculated stress and the measured strain, modulus updating is done element-by-element based on Hooke's law. Breast tissue modulus reconstruction using simulated data and phantom modulus reconstruction using experimental data indicate that the technique is robust.

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Ultrasound Imaging

Rao¹

2002

Encyclopedia of Imaging Science and Technology

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Ultrasound is defined as sound waves whose frequency is above 20 kHz, the upper limit of the human audible range. The past century has witnessed the growth of an imaging technology that uses ultrasound as the information carrier. A physical medium is required to sustain longitudinal and transverse ultrasound waves. The imaging can be passive, when the object to be detected is the source of sound, or active, when an external deliberately controlled source of sound is used and the echoes from objects in the medium are used to generate an image. State‐of‐the‐art active systems can launch waves into a medium and nondestructively collect echo signals and display information pertaining to the inside of an optically opaque three‐dimensional object. In medical applications, the propagation medium is soft tissue. Present day technology permits real‐time (20 or more image frames per second) visualization of the gross anatomy and pathology. Medical ultrasound has found applications throughout the breadth of diagnostic investigations that includes obstetrics, gynecology, abdomen, ophthalmology, cardiovascular system, breast, and superficial structures. Besides medical applications, ultrasound is also used in nondestructive evaluation (NDE) and sound navigation and ranging (SONAR). NDE is commonly used in the aerospace and nuclear power industries to inspect safety‐critical parts for flaws during in‐service use. The medium here is generally solid material. SONAR pertains to imaging under the sea. The imaging techniques and technologies used in these different application areas are quite similar, at least for medical and NDE. Therefore, the main body of the discussion centers on medical imaging. An ultrasound imaging system usually conveys information about echo generating objects. The image can be thought of as a display of the multidimensional spatial distribution of some object‐dependent entity. Visualization of this information is one of the objectives, and perhaps the major objective in medical ultrasound. The image value is generally related to the mechanical or elastic property of the object. A secondary objective therefore is to understand and quantify the relationship between the image value and the object property, also known as quantitative imaging or tissue characterization in medical ultrasound. This area still remains a subject of active research. This article deals only with the first objective. The three steps involved in the imaging process, namely, transduction and reception by the transducer, two‐way propagation in the medium to some depth, and the scattering/reflection phenomenon are considered in detail. Different modes of scanning and information display employed in medical diagnosis and NDE are considered.

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Elastography: A systems approach

Cited by 73 publications

References 8 publications

Algorithms for ultrasound elastography: a survey

Algorithms for ultrasound elastography: a survey

A constrained modulus reconstruction technique for breast cancer assessment

Ultrasound Imaging

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