Spatiotemporal Clutter Filtering of Ultrafast Ultrasound Data Highly Increases Doppler and fUltrasound Sensitivity

Abstract

Ultrafast ultrasonic imaging is a rapidly developing field based on the unfocused transmission of plane or diverging ultrasound waves. This recent approach to ultrasound imaging leads to a large increase in raw ultrasound data available per acquisition. Bigger synchronous ultrasound imaging datasets can be exploited in order to strongly improve the discrimination between tissue and blood motion in the field of Doppler imaging. Here we propose a spatiotemporal singular value decomposition clutter rejection of ultrasonic data acquired at ultrafast frame rate. The singular value decomposition (SVD) takes benefits of the different features of tissue and blood motion in terms of spatiotemporal coherence and strongly outperforms conventional clutter rejection filters based on high pass temporal filtering. Whereas classical clutter filters operate on the temporal dimension only, SVD clutter filtering provides up to a four-dimensional approach (3D in space and 1D in time). We demonstrate the performance of SVD clutter filtering with a flow phantom study that showed an increased performance compared to other classical filters (better contrast to noise ratio with tissue motion between 1 and 10mm/s and axial blood flow as low as 2.6 mm/s). SVD clutter filtering revealed previously undetected blood flows such as microvascular networks or blood flows corrupted by significant tissue or probe motion artifacts. We report in vivo applications including small animal fUltrasound brain imaging (blood flow detection limit of 0.5 mm/s) and several clinical imaging cases, such as neonate brain imaging, liver or kidney Doppler imaging.

Fast Vascular Ultrasound Imaging With Enhanced Spatial Resolution and Background Rejection

“…The received signal ( , , ) is a superposition of echoes originating from the microbubbles carried by the blood flow and the strong clutter signal originating from the surrounding tissue. Following [21], we model the received IQ signal as…”

“…Different pulse streams and processing algorithms were designed to make use of this physical phenomenon and remove tissue related background from CEUS signals [22]. In addition, different priors on the relatively slow movement of the tissue [23] and its spatial coherence [21] are used in order to design temporal and spatiotemporal (SVD based) filters for tissue clutter removal. Using FIR/IIR filters as in [23], the clutter free movie ̂( , , ) is estimated by removing the quasi static tissue signal.…”

Development and Application of Optical Coherence Tomography (OCT)

“…PS-OCT also enables the segmentation of structures based on common polarization properties and the determination of interfaces between different tissue segments based on changing polarization properties. Segmentation and image feature assessment was developed based on depolarization [20,103,[121][122][123][124][125] and birefringence [98,116,[126][127][128][129]. Practical examples of PS-OCT applications will be shown in the following sections.…”

“…(a) Reflectivity B-scan; (b) DOPU B-scan (color map: 0-1); (c) Depolarization in the retinal pigment epithelium (RPE, red) and choroid (green) overlaid on reflectivity image; (d) Fundus map indicating thickness of depolarizing pixels at the level of the RPE; (e) Relation of DOPU and melanin density assessed by histology in RPE/choroid of rat eyes (adapted with permission from [26], ARVO, 2015). (f,g) PS-OCT based layer segmentation in an AMD patient with drusen (adapted with permission from [121], SPIE, 2010). (f) Reflectivity B-scan with segmented inner limiting membrane (blue), RPE (red), and Bruch's membrane (green).…”

Localisation of multiple non-isolated microbubbles with frequency decomposition in super-resolution imaging

“…The first stage was a spatio-temporal filtering to remove the tissue echoes from the acquired frames and generate a contrast-mode image [11]. The second stage was zero-phase filtering with a frequency range of 2 − 7.5 MHz according to the ultrasound probe bandwidth.…”