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Nemirovsky-Rotman S, Friedman Z, Fischer D, Chernihovsky A, Sharbel K, Porat M. Simultaneous compression and speckle reduction of clinical breast and fetal ultrasound images using rate-fidelity optimized coding. ULTRASONICS 2021; 110:106229. [PMID: 33091651 DOI: 10.1016/j.ultras.2020.106229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 06/22/2020] [Accepted: 07/14/2020] [Indexed: 06/11/2023]
Abstract
Medical ultrasound images are inherently noised with speckle noise, which may interfere with Computer Aided Diagnostics (CAD) tasks, such as automatic segmentation. A compression and speckle de-noising method is proposed and tested on real clinical breast and fetal ultrasound images. The proposed algorithm is based on the optimization of quantization coefficients when applying Wavelet representation on the image, where the optimization is held such that a pre-defined mathematical fidelity criterion with respect to a desired de-speckled image is obtained. The proposed algorithm yields effective speckle reduction whilst preserving the edges in the images, with a reduced computational burden compared to other existing state-of-the-art methods, such as Optimal Bayesian Non-Local Means (OBNLM). In addition, the images are simultaneously compressed to a target bit-rate. The proposed algorithm is evaluated using both objective mathematical fidelity criteria (such as Structural Similarity and Edge Preserve) as well as subjective radiologists tests. The experimental results demonstrate the ability of the proposed method to achieve de-speckled images with compression ratios of approximately 30:1, whilst obtaining competitive subjective as well as objective fidelity measures with respect to the desired de-speckled images.
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Affiliation(s)
| | - Z Friedman
- Faculty of Biomedical Engineering, Technion, Israel
| | - D Fischer
- Dept. of Radiology in Galilee Medical Center, Israel
| | | | - K Sharbel
- Dept. of Radiology in Galilee Medical Center, Israel
| | - M Porat
- Faculty of Electrical Engineering, Technion, Israel
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Ramadan H, Lachqar C, Tairi H. Saliency-guided automatic detection and segmentation of tumor in breast ultrasound images. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.101945] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Cui W, Li M, Gong G, Lu K, Sun S, Dong F. Guided trilateral filter and its application to ultrasound image despeckling. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2019.101625] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Shuo WBS, Ji-Bin LMD, Ziyin ZMD, John EP. Artificial Intelligence in Ultrasound Imaging: Current Research and Applications. ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY 2019. [DOI: 10.37015/audt.2019.190811] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey. BIOMED RESEARCH INTERNATIONAL 2018; 2018:5137904. [PMID: 29687000 PMCID: PMC5857346 DOI: 10.1155/2018/5137904] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 01/12/2018] [Accepted: 02/06/2018] [Indexed: 12/13/2022]
Abstract
The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system.
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Gear Shifting of Quadriceps during Isometric Knee Extension Disclosed Using Ultrasonography. BIOMED RESEARCH INTERNATIONAL 2018; 2018:6385315. [PMID: 29744360 PMCID: PMC5878899 DOI: 10.1155/2018/6385315] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 01/15/2018] [Accepted: 01/30/2018] [Indexed: 11/24/2022]
Abstract
Ultrasonography has been widely employed to estimate the morphological changes of muscle during contraction. To further investigate the motion pattern of quadriceps during isometric knee extensions, we studied the relative motion pattern between femur and quadriceps under ultrasonography. An interesting observation is that although the force of isometric knee extension can be controlled to change almost linearly, femur in the simultaneously captured ultrasound video sequences has several different piecewise moving patterns. This phenomenon is like quadriceps having several forward gear ratios like a car starting from rest towards maximal voluntary contraction (MVC) and then returning to rest. Therefore, to verify this assumption, we captured several ultrasound video sequences of isometric knee extension and collected the torque/force signal simultaneously. Then we extract the shapes of femur from these ultrasound video sequences using video processing techniques and study the motion pattern both qualitatively and quantitatively. The phenomenon can be seen easier via a comparison between the torque signal and relative spatial distance between femur and quadriceps. Furthermore, we use cluster analysis techniques to study the process and the clustering results also provided preliminary support to the conclusion that, during both ramp increasing and decreasing phases, quadriceps contraction may have several forward gear ratios relative to femur.
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Cong W, Yang J, Ai D, Song H, Chen G, Liang X, Liang P, Wang Y. Global Patch Matching (GPM) for freehand 3D ultrasound reconstruction. Biomed Eng Online 2017; 16:124. [PMID: 29084564 PMCID: PMC5661982 DOI: 10.1186/s12938-017-0411-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Accepted: 10/11/2017] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND 3D ultrasound volume reconstruction from B-model ultrasound slices can provide more clearly and intuitive structure of tissue and lesion for the clinician. METHODS This paper proposes a novel Global Path Matching method for the 3D reconstruction of freehand ultrasound images. The proposed method composes of two main steps: bin-filling scheme and hole-filling strategy. For the bin-filling scheme, this study introduces two operators, including the median absolute deviation and the inter-quartile range absolute deviation, to calculate the invariant features of each voxel in the 3D ultrasound volume. And the best contribution range for each voxel is obtained by calculating the Euclidian distance between current voxel and the voxel with the minimum invariant features. Hence, the intensity of the filling vacant voxel can be obtained by weighted combination of the intensity distribution of pixels in the best contribution range. For the hole-filling strategy, three conditions, including the confidence term, the data term and the gradient term, are designed to calculate the weighting coefficient of the matching patch of the vacant voxel. While the matching patch is obtained by finding patches with the best similarity measure that defined by the three conditions in the whole 3D volume data. RESULTS Compared with VNN, PNN, DW, FMM, BI and KR methods, the proposed Global Path Matching method can restore the 3D ultrasound volume with minimum difference. CONCLUSIONS Experimental results on phantom and clinical data sets demonstrate the effectiveness and robustness of the proposed method for the reconstruction of ultrasound volume.
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Affiliation(s)
- Weijian Cong
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, 100081 China
- School of Computer Science and Engineering, Beihang University, Beijing, 100191 China
| | - Jian Yang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, 100081 China
| | - Danni Ai
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, 100081 China
| | - Hong Song
- School of Software, Beijing Institute of Technology, Beijing, 100081 China
| | - Gang Chen
- Interventional Ultrasound Department, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853 China
| | - Xiaohui Liang
- School of Computer Science and Engineering, Beihang University, Beijing, 100191 China
| | - Ping Liang
- Interventional Ultrasound Department, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853 China
| | - Yongtian Wang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, 100081 China
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Yu S, Wu S, Zhuang L, Wei X, Sak M, Neb D, Hu J, Xie Y. Efficient Segmentation of a Breast in B-Mode Ultrasound Tomography Using Three-Dimensional GrabCut (GC3D). SENSORS (BASEL, SWITZERLAND) 2017; 17:E1827. [PMID: 28786946 PMCID: PMC5580039 DOI: 10.3390/s17081827] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 08/01/2017] [Accepted: 08/04/2017] [Indexed: 01/14/2023]
Abstract
As an emerging modality for whole breast imaging, ultrasound tomography (UST), has been adopted for diagnostic purposes. Efficient segmentation of an entire breast in UST images plays an important role in quantitative tissue analysis and cancer diagnosis, while major existing methods suffer from considerable time consumption and intensive user interaction. This paper explores three-dimensional GrabCut (GC3D) for breast isolation in thirty reflection (B-mode) UST volumetric images. The algorithm can be conveniently initialized by localizing points to form a polygon, which covers the potential breast region. Moreover, two other variations of GrabCut and an active contour method were compared. Algorithm performance was evaluated from volume overlap ratios ( T O , target overlap; M O , mean overlap; F P , false positive; F N , false negative) and time consumption. Experimental results indicate that GC3D considerably reduced the work load and achieved good performance ( T O = 0.84; M O = 0.91; F P = 0.006; F N = 0.16) within an average of 1.2 min per volume. Furthermore, GC3D is not only user friendly, but also robust to various inputs, suggesting its great potential to facilitate clinical applications during whole-breast UST imaging. In the near future, the implemented GC3D can be easily automated to tackle B-mode UST volumetric images acquired from the updated imaging system.
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Affiliation(s)
- Shaode Yu
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
- Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China.
| | - Shibin Wu
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
- Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China.
| | - Ling Zhuang
- Department of Oncology, the Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201, USA.
| | - Xinhua Wei
- Department of Radiology, Guangzhou first Hospital, Guangzhou Medical University, Guangzhou 510180, China.
| | - Mark Sak
- Department of Oncology, the Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201, USA.
- Delphinus Medical Technologies, Inc., Plymouth, Detroit, MI 46701, USA.
| | - Duric Neb
- Department of Oncology, the Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201, USA.
- Delphinus Medical Technologies, Inc., Plymouth, Detroit, MI 46701, USA.
| | - Jiani Hu
- Department of Radiology, Wayne State University, Detroit, MI 48201, USA.
| | - Yaoqin Xie
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
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A Review on Real-Time 3D Ultrasound Imaging Technology. BIOMED RESEARCH INTERNATIONAL 2017; 2017:6027029. [PMID: 28459067 PMCID: PMC5385255 DOI: 10.1155/2017/6027029] [Citation(s) in RCA: 99] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 03/07/2017] [Indexed: 01/06/2023]
Abstract
Real-time three-dimensional (3D) ultrasound (US) has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations. Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional (2D) probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail.
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