scholarly journals Convergence Gain in Compressive Deconvolution: Application to Medical Ultrasound Imaging

2018 ◽  
Vol 8 (12) ◽  
pp. 2558 ◽  
Author(s):  
Bin Gao ◽  
Shaozhang Xiao ◽  
Li Zhao ◽  
Xian Liu ◽  
Kegang Pan
Keyword(s):  
Image Reconstruction ◽  
Splitting Method ◽  
Ultrasound Image ◽  
Synthetic Data ◽  
Quadratic Term ◽  
Ultrasound Images ◽  
Closed Form Solutions ◽  
Medical Ultrasound Imaging ◽  
Partial Linearization

The compressive deconvolution (CD) problem represents a class of efficient models that is appealing in high-resolution ultrasound image reconstruction. In this paper, we focus on designing an improved CD method based on the framework of a strictly contractive Peaceman–Rechford splitting method (sc-PRSM). By fully excavating the special structure of ultrasound image reconstruction, the improved CD method is easier to implement by partially linearizing the quadratic term of subproblems in the CD problem. The resulting subproblems can obtain closed-form solutions. The convergence of the improved CD method with partial linearization is guaranteed by employing a customized relaxation factor. We establish the global convergence for the new method. The performance of the method is verified via several experiments implemented in realistic synthetic data and in vivo ultrasound images.

scholarly journals Enhancing ultrasound texture differences for developing an in vivo 'virtual histology' approach to bovine ovarian imaging

2007 ◽  
Vol 19 (8) ◽  
pp. 910 ◽  
Author(s):  
Mark G. Eramian ◽  
Gregg P. Adams ◽  
Roger A. Pierson
Keyword(s):  
Image Processing ◽  
Ultrasound Image ◽  
Ultrasound Images ◽  
Virtual Histology ◽  
Form And Function ◽  
Non Invasive ◽  
Candidate Image ◽  
And Function ◽  
Processing Techniques

A ‘virtual histology’ can be thought of as the ‘staining’ of a digital ultrasound image via image processing techniques in order to enhance the visualisation of differences in the echotexture of different types of tissues. Several candidate image-processing algorithms for virtual histology using ultrasound images of the bovine ovary were studied. The candidate algorithms were evaluated qualitatively for the ability to enhance the visual differences in intra-ovarian structures and quantitatively, using standard texture description features, for the ability to increase statistical differences in the echotexture of different ovarian tissues. Certain algorithms were found to create textures that were representative of ovarian micro-anatomical structures that one would observe in actual histology. Quantitative analysis using standard texture description features showed that our algorithms increased the statistical differences in the echotexture of stroma regions and corpus luteum regions. This work represents a first step toward both a general algorithm for the virtual histology of ultrasound images and understanding dynamic changes in form and function of the ovary at the microscopic level in a safe, repeatable and non-invasive way.

Prosthetic socket design system using ultrasound image : Reconstruction of volume data from ultrasound images

2004 ◽  
Vol 2004.16 (0) ◽  
pp. 171-172
Author(s):  
Hiroshi OTSUKA ◽  
Hiroshi OCHIAI ◽  
Tomohiko KIHARA ◽  
Shinichiro YAMAMOTO ◽  
Hiroyuki KOYAMA ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Ultrasound Image ◽  
Design System ◽  
Ultrasound Images ◽  
Volume Data ◽  
Prosthetic Socket

scholarly journals Fully automated algorithm estimates muscle fascicle length from ultrasound image

2020 ◽  
Author(s):  
Tim J. van der Zee ◽  
Arthur D. Kuo
Keyword(s):  
Feature Detection ◽  
Vastus Lateralis ◽  
Ultrasound Image ◽  
Vastus Lateralis Muscle ◽  
Ultrasound Images ◽  
Fascicle Length ◽  
Muscle Fascicle ◽  
Cyclic Movements ◽  
Automated Algorithms

AbstractWhile ultrasound is a useful tool for visualizing muscle in vivo, traditional analysis involves substantial manual labor. Semi-automated algorithms have been introduced in recent years, reducing the amount of time required for extracting pennation angles and fascicle lengths from ultrasound images. Unfortunately, semi-automated algorithms still require some user actions and thereby subjective decision making. We here present a freely available, fully automated feature detection algorithm that involves Hessian filtering to highlight line-like objects within the ultrasound image. Hough transform is used to determine muscle fascicle angles and feature detection is used to determine the location and angle of aponeuroses. As a demonstration, we test the algorithm on ultrasound images obtained from vastus lateralis muscle in healthy individuals (N = 9) during isometric knee extension moment production (0 – 45 N-m) at three knee angles (15-25 deg). Pennation angle, muscle thickness and fascicle length vary with knee moment and knee angle in line with previous observations. Specifically, fascicle length decreases with larger knee moments and increases towards knee flexion. We expect the proposed algorithm to be useful for estimating muscle fascicle lengths during cyclic movements like human locomotion.

scholarly journals Ultrasonography of the Cervical Spine

2014 ◽  
Vol 120 (1) ◽  
pp. 86-96 ◽  
Author(s):  
Maarten van Eerd ◽  
Jacob Patijn ◽  
Judith M. Sieben ◽  
Mischa Sommer ◽  
Jan Van Zundert ◽  
...  
Keyword(s):  
Cervical Spine ◽  
Cervical Vertebrae ◽  
Intraclass Correlation ◽  
Ultrasound Image ◽  
Mastoid Process ◽  
Ultrasound Images ◽  
Anatomical Landmarks ◽  
Bony Landmarks

Abstract Background: Anatomical validation studies of cervical ultrasound images are sparse. Validation is crucial to ensure accurate interpretation of cervical ultrasound images and to develop standardized reliable ultrasound procedures to identify cervical anatomical structures. The aim of this study was to acquire validated ultrasound images of cervical bony structures and to develop a reliable method to detect and count the cervical segmental levels. Methods: An anatomical model of a cervical spine, embedded in gelatin, was inserted in a specially developed measurement device. This provided ultrasound images of cervical bony structures. Anatomical validation was achieved by laser light beams projecting the center of the ultrasound image on the cervical bony structures through a transparent gelatin. Results: Anatomically validated ultrasound images of different cervical bony structures were taken from dorsal, ventral, and lateral perspectives. Potentially relevant anatomical landmarks were defined and validated. Test/retest analysis for positioning showed a reproducibility with an intraclass correlation coefficient for single measures of 0.99. Besides providing validated ultrasound images of bony structures, this model helped to develop a method to detect and count the cervical segmental levels in vivo at long-axis position, in a dorsolateral (paramedian) view at the level of the laminae, starting from the base of the skull and sliding the ultrasound probe caudally. Conclusions: Ultrasound bony images of the cervical vertebrae were validated with an in vitro model. Anatomical bony landmarks are the mastoid process, the transverse process of C1, the tubercles of C6 and C7, and the cervical laminae. Especially, the cervical dorsal laminae serve best as anatomical bony landmarks to reliably detect the cervical segmental levels in vivo.

scholarly journals Mutually Orthogonal Golay Complementary Sequences in Synthetic Aperture Imaging Systems

2015 ◽  
Vol 40 (2) ◽  
pp. 283-289 ◽  
Author(s):  
Ihor Trots
Keyword(s):  
Image Reconstruction ◽  
Signal To Noise Ratio ◽  
Ultrasound Image ◽  
Image Resolution ◽  
Synthetic Aperture ◽  
Single Element ◽  
Ultrasound Images ◽  
Transducer Array ◽  
Linear Transducer ◽  
Medical Diagnostic

Abstract The main objective of this study is to improve the ultrasound image by employing a new algorithm based on transducer array element beam pattern correction implemented in the synthetic transmit aperture (STA) method combined with emission of mutually orthogonal complementary Golay sequences. Orthogonal Golay sequences can be transmitted and received by different transducer elements simultaneously, thereby decreasing the time of image reconstruction, which plays an important role in medical diagnostic imaging. The paper presents the preliminary results of computer simulation of the synthetic aperture method combined with the orthogonal Golay sequences in a linear transducer array. The transmission of long waveforms characterized by a particular autocorrelation function allows to increase the total energy of the transmitted signal without increasing the peak pressure. It can also improve the signal-to-noise ratio and increase the visualization depth maintaining the ultrasound image resolution. In the work, the 128-element linear transducer array with a 0.3 mm pitch excited by 8-bits Golay coded sequences as well as one cycle at nominal frequencies of 4 MHz were used. The comparison of 2D ultrasound images of the phantoms is presented to demonstrate the benefits of a coded transmission. The image reconstruction was performed using the synthetic STA algorithm with transmit and receive signals correction based on a single element directivity function.

Performance Evaluation of Adaptive Imaging Based on Multiphase Apodization with Cross-correlation: A Pilot Study in Abdominal Ultrasound

2018 ◽  
Vol 40 (4) ◽  
pp. 195-214
Author(s):  
Junseob Shin ◽  
Yu Chen ◽  
Harshawn Malhi ◽  
Frank Chen ◽  
Jesse Yen
Keyword(s):  
Cross Correlation ◽  
Human Subjects ◽  
Vena Cava ◽  
Ultrasound Image ◽  
Abdominal Ultrasound ◽  
Image Contrast ◽  
Ultrasound Images ◽  
Adaptive Imaging ◽  
Weighting Matrix

Degradation of image contrast caused by phase aberration, off-axis clutter, and reverberation clutter remains one of the most important problems in abdominal ultrasound imaging. Multiphase apodization with cross-correlation (MPAX) is a novel beamforming technique that enhances ultrasound image contrast by adaptively suppressing unwanted acoustic clutter. MPAX employs multiple pairs of complementary sinusoidal phase apodizations to intentionally introduce grating lobes that can be used to derive a weighting matrix, which mostly preserves the on-axis signals from tissue but reduces acoustic clutter contributions when multiplied with the beamformed radio-frequency (RF) signals. In this paper, in vivo performance of the MPAX technique was evaluated in abdominal ultrasound using data sets obtained from 10 human subjects referred for abdominal ultrasound at the USC Keck School of Medicine. Improvement in image contrast was quantified, first, by the contrast-to-noise ratio (CNR) and, second, by the rating of two experienced radiologists. The MPAX technique was evaluated for longitudinal and transverse views of the abdominal aorta, the inferior vena cava, the gallbladder, and the portal vein. Our in vivo results and analyses demonstrate the feasibility of the MPAX technique in enhancing image contrast in abdominal ultrasound and show potential for creating high contrast ultrasound images with improved target detectability and diagnostic confidence.

scholarly journals Development of a semi-automated segmentation tool for high frequency ultrasound image analysis of mouse echocardiograms

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kristi Powers ◽  
Raymond Chang ◽  
Justin Torello ◽  
Rhonda Silva ◽  
Yannick Cadoret ◽  
...  
Keyword(s):  
Image Analysis ◽  
Automated Analysis ◽  
Structure And Function ◽  
Ultrasound Images ◽  
Cardiac Structure ◽  
Short Axis ◽  
Pixel Intensity ◽  
Cardiac Structure And Function ◽  
And Function

AbstractEchocardiography is a widely used and clinically translatable imaging modality for the evaluation of cardiac structure and function in preclinical drug discovery and development. Echocardiograms are among the first in vivo diagnostic tools utilized to evaluate the heart due to its relatively low cost, high throughput acquisition, and non-invasive nature; however lengthy manual image analysis, intra- and inter-operator variability, and subjective image analysis presents a challenge for reproducible data generation in preclinical research. To combat the image-processing bottleneck and address both variability and reproducibly challenges, we developed a semi-automated analysis algorithm workflow to analyze long- and short-axis murine left ventricle (LV) ultrasound images. The long-axis B-mode algorithm executes a script protocol that is trained using a reference library of 322 manually segmented LV ultrasound images. The short-axis script was engineered to analyze M-mode ultrasound images in a semi-automated fashion using a pixel intensity evaluation approach, allowing analysts to place two seed-points to triangulate the local maxima of LV wall boundary annotations. Blinded operator evaluation of the semi-automated analysis tool was performed and compared to the current manual segmentation methodology for testing inter- and intra-operator reproducibility at baseline and after a pharmacologic challenge. Comparisons between manual and semi-automatic derivation of LV ejection fraction resulted in a relative difference of 1% for long-axis (B-mode) images and 2.7% for short-axis (M-mode) images. Our semi-automatic workflow approach reduces image analysis time and subjective bias, as well as decreases inter- and intra-operator variability, thereby enhancing throughput and improving data quality for pre-clinical in vivo studies that incorporate cardiac structure and function endpoints.

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