Ultrasound elastography (UE) is a promising imaging modality [1]. In vascular applications it uses ultrasound images of
arteries in motion to assess their mechanical parameters and stress distributions in physiological or interventional loading
conditions [2]. However some simplifying assumptions adopted classically in UE image processing methods restrict this
modality to strain imaging.
This work presents a new UE image processing method based on differential optical flow. The method constrains the
solution of the optical flow problem to minimize a mechanical potential energy. In other words, from all possible
solutions of the optical flow problem, it determines the one that minimizes strain energy density of the tissue.
In addition, in order to estimate concurrently the stiffness parameter of the tissue with its optical flow (or apparent
displacement field); we constrain them to verify the tissue mechanical equilibrium equations.
In principle, with this approach we can assess the strain field and map the stiffness parameter for an elastic tissue.
Finally our approach also allows us to estimate mechanical parameters of strained phantoms, from their RF or B-mode
ultrasound images, considering not only the usual linear elastic mechanical law but also hyperelastic ones.
Optical coherence tomography (OCT) is a powerful, noninvasive biomedical technique that uses low-coherence light sources to obtain in-depth scans of biological tissues. We report results obtained with three different sources emitting at 1570, 1330, and 810 nm, respectively. Attenuation and backscattering measurements are obtained with these sources for several in vitro biological tissues. From these measurements, we use a graphical method to make comparisons of the penetration depth and backscattering intensity of each wavelength for the studied samples. The influence of the coherence length of each source is also taken into account in order to make a more relevant comparison.
The objective of this study is to investigate the feasibility of elastographic monitoring of High Intensity Focused Ultrasound (HIFU) therapy of prostate cancer. Elastography is an imaging technique based on strain estimation in soft tissues under quasi-static compression. Since pathological tissues and HIFU-induced lesions exhibit different elastic properties than normal tissues, elastography is potentially able to achieve these goals. An ultrasound scanner was connected to a PC to acquire RF images. This setup is compatible with a HIFU device used for prostate cancer therapy by transrectal route. The therapy transducer and the biplane-imaging probe are covered with a balloon filled with a coupling liquid. Compression of the prostate is applied by inflating the balloon, while imaging sector scans of the prostate. In-vivo elastograms of the prostate were acquired before HIFU treatment. Problems inherent to in-vivo acquisitions are reported, such as undesired tangential displacements during the radial compression. This study shows the potential for in-vivo elastogram acquisition of HIFU-induced lesions in the human prostate.
One technique of elasticity imaging, elastography, uses cross- correlation between two ultrasound A-lines to obtain an axial strain image of a sample. Usually, great care is taken with respect to the assumption that the response of the sample is elastic (lossless). In this paper, we relax this assumption and extend elastography to estimate the time-varying displacement and strain status of small samples (of the order of 1 mm). Results are presented for gel phantoms and articular cartilage samples, and they are consistent with the current theories of poroelastic materials. For example, an effective Poisson's ratio of approximately 0.5 obtained at ramp completion indicates volume conservation since the ramp time was much shorter than the characteristic relaxation time of the material. Subsequent reduction in effective Poisson's ratio coincident with stress-relaxation confirms poroelastic mechanisms whereby fluid exudation dissipates internal fluid pressurization. Observed slower relaxation of strain at the center of the sample is also compatible with these types of models. Preliminary data obtained with articular cartilage also shows valuable potential of this technique to investigate tissue biomechanics.
In this paper, we present an optical flow method to infer the blood flow in arteries by tracking the contrast medium in angiography. in our approach, the velocity field is constrained to be parabolic to take into account this particular property of laminar blood flows. With this method, we get several parameters, both hemodynamic and geometric: the artery radius, the maximum velocity, the blood flow, the centerline position of the artery and other related ones. Tests of the algorithm were conducted on simulated cineangiographic images of straight and stenotic vessels and show errors ranging from 1 percent of straight vessels and up to 10 percent for short stenosis. Preliminary results with femoral arteries are also very encouraging.
The purpose of this paper is to elaborate a novel method to determine the absolute geometry of a biplane x-ray imaging system, using angiograms acquired daily by the clinician, without any special calibration procedure during the x-ray examination. The approach is based on the minimization of the mean square distance between observed and predicted projections of a set of reference points identified by the clinician on a simultaneous pair of images. The method employed is iterative and needs two views of at least 12 reference points of unknown 3-D positions to converge to the correct answer. Our approach should be particularly useful in clinical applications since it needs very little intervention from the clinician.
In this paper, we propose a new approach to evaluate the ventricle dynamics in monoplane ventriculography. The approach is divided into two main steps: first, the 2D image plane motion (x,y motions) of the heart is evaluated and next the depth motion (z motion) is estimated. To compute the x,y motions we use two methods: first a radial method in which regional wall motion is assumed to converge toward the image center of the left ventricle and second, a computer vision method named optical flow. These methods are applied to the segmented ventriculograms that are obtained by setting to 0 and 1 the exterior and interior respectively of the ventricle using an edge detection algorithm. From the x,y motions, one can align (register) two consecutive original ventriculograms in a manner to make the ventricle contours meet exactly. This operation is done with a gray level bilinear interpolation technique that actually remove the x and y motion components between the two frames. If one assumes that the contrast medium has a constant concentration and is uniformly distributed in the ventricle then the brightness difference between the aligned ventriculograms is directly related to the z motion. Using a pseudo-color image to display this third component of the ventricle motion, one is able to display the 3D motion of the left ventricle. Results are presented for an ellipsoid model of the ventricle undergoing different contraction behaviors and for a clinical example.
In this paper, physical constraints are used to adapt known optical flow algorithms to study blood circulation in healthy and stenosed arteries by tracking dye dispersion using radiological image sequences. To this end, the penalty functional method of constrained optimization is put forward. Simulated radiological images taking into account blood flow and contrast medium dispersion are computed to test the proposed algorithms. Results from these simulated radiological images are presented and discussed.
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