Noise robust one-dimensional blind deconvolution of medical ultrasound images

1999 ◽  
Vol 46 (2) ◽  
pp. 291-299 ◽  
Author(s):  
T. Taxt ◽  
G.V. Frolova
Keyword(s):  
Blind Deconvolution ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
One Dimensional ◽  
Noise Robust

Deconvolution of in-Vivo Ultrasound B-Mode Images

1993 ◽  
Vol 15 (2) ◽  
pp. 122-133 ◽  
Author(s):  
Jørgen Arendt Jensen ◽  
Jan Mathorne ◽  
Torben Gravesen ◽  
Bjarne Stage
Keyword(s):  
Portal Vein ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Axial Resolution ◽  
One Dimensional ◽  
Rf Signal ◽  
Ultrasound Pulse

An algorithm for deconvolution of medical ultrasound images is presented. The procedure involves estimation of the basic one-dimensional ultrasound pulse, determining the ratio of the covariance of the noise to the covariance of the reflection signal, and finally deconvolution of the rf signal from the transducer. Using pulse and covariance estimators makes the approach self-calibrating, as all parameters for the procedure are estimated from the patient under investigation. An example of use on a clinical, in-vivo image is given. A 2 × 2 cm region of the portal vein in a liver is deconvolved. An increase in axial resolution by a factor of 2.4 is obtained. The procedure can also be applied to whole images, when it is ensured that the rf signal is properly measured. A method for doing that is outlined.

scholarly journals Motion blur invariant for estimating motion parameters of medical ultrasound images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Barmak Honarvar Shakibaei Asli ◽  
Yifan Zhao ◽  
John Ahmet Erkoyuncu
Keyword(s):  
Image Quality Assessment ◽  
Medical Image Analysis ◽  
Main Idea ◽  
Delta Function ◽  
Motion Blur ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Fetal Ultrasound ◽  
Dirac Delta ◽  
Motion Parameters

AbstractHigh-quality medical ultrasound imaging is definitely concerning motion blur, while medical image analysis requires motionless and accurate data acquired by sonographers. The main idea of this paper is to establish some motion blur invariant in both frequency and moment domain to estimate the motion parameters of ultrasound images. We propose a discrete model of point spread function of motion blur convolution based on the Dirac delta function to simplify the analysis of motion invariant in frequency and moment domain. This model paves the way for estimating the motion angle and length in terms of the proposed invariant features. In this research, the performance of the proposed schemes is compared with other state-of-the-art existing methods of image deblurring. The experimental study performs using fetal phantom images and clinical fetal ultrasound images as well as breast scans. Moreover, to validate the accuracy of the proposed experimental framework, we apply two image quality assessment methods as no-reference and full-reference to show the robustness of the proposed algorithms compared to the well-known approaches.

A Novel Despeckling Method for Medical Ultrasound Images Based on the Nonsubsampled Shearlet and Guided Filter

2019 ◽  
Vol 39 (3) ◽  
pp. 1449-1470 ◽  
Author(s):  
Ju Zhang ◽  
Xiaojie Xiu ◽  
Jun Zhou ◽  
Kailun Zhao ◽  
Zheng Tian ◽  
...  
Keyword(s):  
Guided Filter ◽  
Ultrasound Images ◽  
Medical Ultrasound
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