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.
Highlights
Imaging plays a key role in cancer screening, early diagnosis, and monitoring of disease progression
The proposed algorithm was tested on a custom-made flow phantom and data set, as well as data from eight subjects with various abnormalities, that is, five breast lesions, which included benign breast fibroadenoma, malignant invasive ductal carcinoma (IDC) with grades II and III, metastatic renal cell carcinoma, two benign and malignant thyroid nodules, and two pathological liver subjects
Non‐contrast using frame rate plane‐wave imaging and tissue clutter the additional background noise that role remains after clutter of filtering can obstruct the small vessels and removal techniques can play a major in visualization neovascularization in tumors
Summary
Imaging plays a key role in cancer screening, early diagnosis, and monitoring of disease progression. Contrast-enhanced digital mammography [3]; contrast-enhanced magnetic resonance imaging [4]; diffuse optical imaging [5]; micro-computed tomography [6]; and, more recently, photoacoustic computed tomography [7] and contrast-enhanced ultrasound imaging [8] are the imaging techniques known to visualize the vascularity of the tumor, for breast cancer in particular. They are limited by the use of an exogenous contrast agent, radiation exposure, and cost burden. The main challenge of removing background noise in power Doppler images is preserving the.
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