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Sensors 2019, 19(2), 245; https://doi.org/10.3390/s19020245

Non-Local Based Denoising Framework for In Vivo Contrast-Free Ultrasound Microvessel Imaging

1
Department of Radiology, Mayo Clinic College of Medicine & Science, Rochester, MN 55905, USA
2
Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine & Science, Rochester, MN 55905, USA
*
Author to whom correspondence should be addressed.
Received: 11 December 2018 / Revised: 3 January 2019 / Accepted: 4 January 2019 / Published: 10 January 2019
(This article belongs to the Section Biosensors)
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Abstract

Vascular networks can provide invaluable information about tumor angiogenesis. Ultrafast Doppler imaging enables ultrasound to image microvessels by applying tissue clutter filtering methods on the spatio-temporal data obtained from plane-wave imaging. However, the resultant vessel images suffer from background noise that degrades image quality and restricts vessel visibilities. In this paper, we addressed microvessel visualization and the associated noise problem in the power Doppler images with the goal of achieving enhanced vessel-background separation. We proposed a combination of patch-based non-local mean filtering and top-hat morphological filtering to improve vessel outline and background noise suppression. We tested the proposed method on a flow phantom, as well as in vivo breast lesions, thyroid nodules, and pathologic liver from human subjects. The proposed non-local-based framework provided a remarkable gain of more than 15 dB, on average, in terms of contrast-to-noise and signal-to-noise ratios. In addition to improving visualization of microvessels, the proposed method provided high quality images suitable for microvessel morphology quantification that may be used for diagnostic applications. View Full-Text
Keywords: medical imaging; Doppler microvessel imaging; noise suppression; non-local based denoising; singular value decomposition medical imaging; Doppler microvessel imaging; noise suppression; non-local based denoising; singular value decomposition
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Adabi, S.; Ghavami, S.; Fatemi, M.; Alizad, A. Non-Local Based Denoising Framework for In Vivo Contrast-Free Ultrasound Microvessel Imaging. Sensors 2019, 19, 245.

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