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Applied Sciences
Special Issues
Advanced Biomedical Ultrasound Imaging Techniques
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Advanced Biomedical Ultrasound Imaging Techniques

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 5069

Special Issue Editors

Prof. Dr. Marvin M. Doyley

E-Mail Website
Guest Editor
Hajim School of Engineering and Applied Sciences, University of Rochester, Rochester, NY, USA
Interests: ultrasound; magnetic resonance imaging; contrast imaging; inverse problem
Dr. Amirtaha Taebi

E-Mail Website
Guest Editor
Department of Biomedical Engineering, University of California, Davis, CA 95616, USA
Interests: biomedical signal and image processing; noninvasive physiological monitoring; medical instrumentation; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Himanshu Shekhar

E-Mail Website
Guest Editor
Department of Internal Medicine, Division of Cardiovascular Diseases, University of Cincinnati, Cincinnati, OH, USA
Interests: image-guided therapy; contrast-enhanced ultrasound; ultrasound-mediated therapeutic delivery; molecular imaging
Dr. Rohit Nayak

E-Mail Website
Guest Editor
Radiology, Mayo Clinic
Interests: ultrasound elastography and_beam forming; compressive sensing_and signal processing

Special Issue Information

Dear Colleagues,

During the last decade, we have witnessed several breakthroughs in diagnostic ultrasound. These discoveries include super-resolution imaging, ultrafast imaging, photoacoustic imaging, and functional imaging, to name a few. Findings that should soon allow clinicians to use ultrasound to perform molecular and functional imaging, tasks once reserved for magnetic resonance imaging, positron emission tomography. As Guest Editor, I would like to invite authors to contribute original research or reviews to a Special Issue on "Advanced Biomedical Ultrasound Imaging Techniques" that focuses on optimizing, improving, and translating emerging ultrasound imaging techniques in the clinical setting.

Prof. Dr. Marvin M. Doyley
Dr. Amirtaha Taebi
Dr. Himanshu Shekhar
Dr. Rohit Nayak
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Super-resolution imaging
  • Photo-Acoustic imaging
  • Quantitative ultrasound
  • Ultrasound tomography
  • Ultrafast imaging
  • 4D imaging
  • Magnetomotive imaging
  • Harmonic and contrast imaging
  • Shear wave imaging

Published Papers (2 papers)

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Research

16 pages, 6053 KiB  
Article
Accelerating 3-D GPU-based Motion Tracking for Ultrasound Strain Elastography Using Sum-Tables: Analysis and Initial Results
by Bo Peng, Shasha Luo, Zhengqiu Xu and Jingfeng Jiang
Appl. Sci. 2019, 9(10), 1991; https://doi.org/10.3390/app9101991 - 15 May 2019
Cited by 5 | Viewed by 2289
Abstract
Now, with the availability of 3-D ultrasound data, a lot of research efforts are being devoted to developing 3-D ultrasound strain elastography (USE) systems. Because 3-D motion tracking, a core component in any 3-D USE system, is computationally intensive, a lot of efforts [...] Read more.
Now, with the availability of 3-D ultrasound data, a lot of research efforts are being devoted to developing 3-D ultrasound strain elastography (USE) systems. Because 3-D motion tracking, a core component in any 3-D USE system, is computationally intensive, a lot of efforts are under way to accelerate 3-D motion tracking. In the literature, the concept of Sum-Table has been used in a serial computing environment to reduce the burden of computing signal correlation, which is the single most computationally intensive component in 3-D motion tracking. In this study, parallel programming using graphics processing units (GPU) is used in conjunction with the concept of Sum-Table to improve the computational efficiency of 3-D motion tracking. To our knowledge, sum-tables have not been used in a GPU environment for 3-D motion tracking. Our main objective here is to investigate the feasibility of using sum-table-based normalized correlation coefficient (ST-NCC) method for the above-mentioned GPU-accelerated 3-D USE. More specifically, two different implementations of ST-NCC methods proposed by Lewis et al. and Luo-Konofagou are compared against each other. During the performance comparison, the conventional method for calculating the normalized correlation coefficient (NCC) was used as the baseline. All three methods were implemented using compute unified device architecture (CUDA; Version 9.0, Nvidia Inc., CA, USA) and tested on a professional GeForce GTX TITAN X card (Nvidia Inc., CA, USA). Using 3-D ultrasound data acquired during a tissue-mimicking phantom experiment, both displacement tracking accuracy and computational efficiency were evaluated for the above-mentioned three different methods. Based on data investigated, we found that under the GPU platform, Lou-Konofaguo method can still improve the computational efficiency (17–46%), as compared to the classic NCC method implemented into the same GPU platform. However, the Lewis method does not improve the computational efficiency in some configuration or improves the computational efficiency at a lower rate (7–23%) under the GPU parallel computing environment. Comparable displacement tracking accuracy was obtained by both methods. Full article
(This article belongs to the Special Issue Advanced Biomedical Ultrasound Imaging Techniques)
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15 pages, 721 KiB  
Article
Convergence Gain in Compressive Deconvolution: Application to Medical Ultrasound Imaging
by Bin Gao, Shaozhang Xiao, Li Zhao, Xian Liu and Kegang Pan
Appl. Sci. 2018, 8(12), 2558; https://doi.org/10.3390/app8122558 - 10 Dec 2018
Cited by 1 | Viewed by 2349
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Advanced Biomedical Ultrasound Imaging Techniques)
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