Literature DB >> 17703671

Performance evaluation of coherence-based adaptive imaging using clinical breast data.

Shun-Li Wang1, Chen-Han Chang, Hsin-Chia Yang, Yi-Hong Chou, Pai-Chi Li.   

Abstract

Sound-velocity inhomogeneities degrade both the spatial resolution and the contrast in diagnostic ultrasound. We previously proposed an adaptive imaging approach based on the coherence of the data received in the channels of a transducer array, and we tested it on phantom data. In this study, the approach was tested on clinical breast data and compared with a correlation-based method that has been widely reported in the literature. The main limitations of the correlation-based method in ultrasonic breast imaging are the use of a near-field, phase-screen model and the integration errors due to the lack of a two-dimensional (2-D) array. In contrast, the proposed coherence-based method adaptively weights each image pixel based on the coherence of the receive-channel data. It does not make any assumption about the source of the focusing errors and has been shown to be effective using 1-D arrays. This study tested its in vivo performance using clinical breast data acquired by a programmable system with a 5 MHz, 128-channel linear array. Twenty-five cases (6 fibroadenomas, 10 carcinomas, 6 cysts, and 3 abscesses) were investigated. Relative to nonweighted imaging, the average improvements in the contrast ratio and contrast-to-noise ratio for the coherence-based method were 8.57 dB and 23.2%, respectively. The corresponding improvements when using the correlation-based method were only 0.42 dB and 3.35%. In an investigated milk-of-calcium case, the improvement in the contrast was 4.47 dB and the axial and lateral dimensions of the object were reduced from 0.39 to 0.32 mm and from 0.51 to 0.43 mm, respectively. These results demonstrate the efficacy of the coherence-based method for clinical ultrasonic breast imaging using 1-D arrays.

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Year:  2007        PMID: 17703671     DOI: 10.1109/tuffc.2007.438

Source DB:  PubMed          Journal:  IEEE Trans Ultrason Ferroelectr Freq Control        ISSN: 0885-3010            Impact factor:   2.725


  9 in total

1.  Enhancing effect of phase coherence factor for improvement of spatial resolution in ultrasonic imaging.

Authors:  Hideyuki Hasegawa
Journal:  J Med Ultrason (2001)       Date:  2015-10-07       Impact factor: 1.314

2.  Robust Short-Lag Spatial Coherence Imaging of Breast Ultrasound Data: Initial Clinical Results.

Authors:  Alycen Wiacek; Ole Marius Hoel Rindal; Eniola Falomo; Kelly Myers; Kelly Fabrega-Foster; Susan Harvey; Muyinatu A Lediju Bell
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2018-11-27       Impact factor: 2.725

3.  Validation of gene expression biomarker analysis for biopsy-based clinical trials in Crohn's disease.

Authors:  Brigid S Boland; David L Boyle; William J Sandborn; Gary S Firestein; Barrett G Levesque; Joshua Hillman; Bing Zhang; James Proudfoot; Lars Eckmann; Peter B Ernst; Jesus Rivera-Nieves; Suresh Pola; Nedret Copur-Dahi; Guangyong Zou; John T Chang
Journal:  Inflamm Bowel Dis       Date:  2015-02       Impact factor: 5.325

Review 4.  Spatial Coherence in Medical Ultrasound: A Review.

Authors:  James Long; Gregg Trahey; Nick Bottenus
Journal:  Ultrasound Med Biol       Date:  2022-03-11       Impact factor: 3.694

5.  Pitch-catch phase aberration correction of multiple isoplanatic patches for 3-D transcranial ultrasound imaging.

Authors:  Brooks D Lindsey; Stephen W Smith
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2013-03       Impact factor: 2.725

6.  Evaluating the robustness of dual apodization with cross-correlation.

Authors:  Chi Hyung Seo; Jesse T Yen
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2009-02       Impact factor: 2.725

7.  Refraction correction in 3D transcranial ultrasound imaging.

Authors:  Brooks D Lindsey; Stephen W Smith
Journal:  Ultrason Imaging       Date:  2014-01       Impact factor: 1.578

8.  Training improvements for ultrasound beamforming with deep neural networks.

Authors:  A C Luchies; B C Byram
Journal:  Phys Med Biol       Date:  2019-02-18       Impact factor: 4.174

9.  Evaluation of Image Reconstruction Algorithms for Confocal Microwave Imaging: Application to Patient Data.

Authors:  Muhammad Adnan Elahi; Declan O'Loughlin; Benjamin R Lavoie; Martin Glavin; Edward Jones; Elise C Fear; Martin O'Halloran
Journal:  Sensors (Basel)       Date:  2018-05-23       Impact factor: 3.576

  9 in total

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