Non-local based denoising framework for in vivo contrast-free ultrasound microvessel imaging

Saba Adabi, Siavash Ghavami, Mostafa Fatemi, Azra Alizad

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish (US)
Article number245
JournalSensors (Switzerland)
Volume19
Issue number2
DOIs
StatePublished - Jan 2 2019

Fingerprint

Microvessels
Image quality
Noise
Ultrasonography
Visualization
Ultrasonics
vessels
Imaging techniques
Visibility
Liver
Tumors
background noise
Signal to noise ratio
Tissue
Doppler Ultrasonography
Thyroid Nodule
Signal-To-Noise Ratio
angiogenesis
nodules
Blood Vessels

Keywords

  • Doppler microvessel imaging
  • Medical imaging
  • Noise suppression
  • Non-local based denoising
  • Singular value decomposition

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

Cite this

Non-local based denoising framework for in vivo contrast-free ultrasound microvessel imaging. / Adabi, Saba; Ghavami, Siavash; Fatemi, Mostafa; Alizad, Azra.

In: Sensors (Switzerland), Vol. 19, No. 2, 245, 02.01.2019.

Research output: Contribution to journalArticle

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