Showing papers by "Adrian Basarab published in 2010"
09 Nov 2010
TL;DR: A comparison between an established (used in magnetic resonance imaging) and a innovative compressed sensing (CS) approach, both adapted to ultrasound (US) imaging, finding the best strategy was a uniform random sampling in the two directions of the spatial RF US image associated with the reconstruction of its k-space.
Abstract: This paper proposes a comparison between an established (used in magnetic resonance imaging) and a innovative compressed sensing (CS) approach, both adapted to ultrasound (US) imaging. Two undersampling patterns suited to US imaging were investigated in each approach on simulated and in vivo radio-frequency US images. Reconstructions of simulated and in vivo US images using CS show minimal information loss. The best strategy (minimising the errors of reconstruction) was a uniform random sampling in the two directions of the spatial RF US image associated with the reconstruction of its k-space.
63 citations
TL;DR: The main ideas and applications behind transverse oscillation images (TO), specific radiofrequency ultrasound images featuring oscillations in both spatial directions, are reviewed, showing how it can improve motion estimation.
44 citations
01 Oct 2010
TL;DR: Three undersampling patterns suited for3D US imaging, together with a nonlinear conjugate gradient reconstruction algorithm of the US image k-spaces, are investigated in vivo radio-frequency 3D US volumes.
Abstract: This paper proposes a compressed sensing method adapted to 3D ultrasound (US) imaging Three undersampling patterns suited for 3D US imaging, together with a nonlinear conjugate gradient reconstruction algorithm of the US image k-spaces, are investigated in vivo radio-frequency 3D US volumes Reconstructions from 50% of the samples of the original 3D volume show little information loss in terms of normalized root mean squared errors
27 citations
TL;DR: The tracking accuracy study shows that tracking errors are larger for the usual cartesian data, whatever the estimation algorithm, indicating that speckle tracking is more reliable when based on the unconverted polar data, and accuracy is improved by using the bilinear deformable block matching (BDBM) algorithm.
18 citations
11 Nov 2010
TL;DR: Results on simulated and experimental data show that this phase-based method for estimating subpixel motion in medical ultrasound imaging provides a better Contrast to Noise Ratio than a classical block-matching method applied to images that are 25 times larger (in number of pixels).
Abstract: This paper presents a phase-based method for estimating subpixel motion in medical ultrasound imaging. The main novelty is to propose a closed form expression for local motion estimation in space domain based on the model of the monogenic signal. First, the proposed method uses the properties of the monogenic signal in order to extract local orientation and phase data of ultrasound images. Second, using these image features, we show how the proposed method can analytically estimate the dense motion field between a pair of images. This way of estimating motion provides subpixel accuracy without interpolating the images. For this reason, we show that the proposed method has high computational efficiency. Results on simulated and experimental data show that this method provides a better Contrast to Noise Ratio than a classical block-matching method applied to images that are 25 times larger (in number of pixels).
17 citations
TL;DR: The goal of this study is to evaluate which method could circumvent the limitations of Doppler methods for evaluation of microcirculation, in the vessels having diameter on the order of 1 mm, using two region-based approaches, one decorrelation-based approach and one spatiotemporal approach.
9 citations
TL;DR: In this paper, the authors compared four vector velocity estimation methods complementary to Doppler, and applied them to six sequences, simulated and experimental, with various flow parameters, and showed specificities of each method.
6 citations
09 Nov 2010
TL;DR: A 3D image model for synthetic static multicellular tumor spheroids is introduced, allowing a more realistic evaluation for the proposed methods, underlining better results with low SNR values.
Abstract: The deblurring of microscopy images has received a lot of attention in past decades, especially with regularisation involving the Total Variation semi-norm. In this paper we propose the evaluation of 3D point spread function space-invariant restauration methods with background estimation for 3D light sheet fluorescence microscopy images. A 3D image model for synthetic static multicellular tumor spheroids is introduced, allowing a more realistic evaluation for the proposed methods, underlining better results with low SNR values. Encouraging results on real data of cancer cells cultured as multicellular tumor spheroids are also presented.
2 citations
01 Oct 2010
TL;DR: In this paper, a 2D least square FIR differentiation filter was proposed in the context of tensorial elastography, which was applied to displacement maps estimated from simulated data and two experimental RF data sets.
Abstract: In this paper, a 2D least square FIR differentiation filter method is proposed in the context of tensorial elastography Displacements are estimated from ultrasonic images obtained during freehand compression Two 2D filters are used for providing all partial derivative maps according to the estimated motion obtained with a Bilinear Deformable Block Matching method From these results, several strain tensor images are built, revealing the tissue's elasticity properties Among these tensors, the infinitesimal strains, the rigid rotation and principal strains tensors are retained, thus improving the contrast between the tumor and the background tissue The 2D filters were first applied to displacement maps estimated from simulated data and two experimental RF data sets and then compared to the 1D differentiation filter LSQSE used in elastography The first experimental data set was collected from a homogeneous phantom with a cylindrical hard inclusion and the second data set was collected from a thyroid gland with a malignant tumor For all studied RF data sets, the contrast between the tumor and the background tissue calculated on strain tensor maps was increased up to a factor of 3 with our method compared to the LSQSE method We also observed that the rigid rotation tensor and principal strains tensor were well adapted to thyroid elastography