Assessment of hybrid speckle reduction algorithms

Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy

Ultrafast ultrasound localization microscopy can be used to detect the subwavelength acoustic scattering of intravenously injected microbubbles to obtain haemodynamic maps of the vasculature of animals and humans. The quality of the haemodynamic maps depends on signal-to-noise ratios and on the algorithms used for the localization of the microbubbles and the rendering of their trajectories. Here we report the results of benchmarking of the performance of seven microbubble-localization algorithms. We used metrics for localization errors, localization success rates, processing times and a measure of the reprojection of the localization of the microbubbles on the original beamformed grid. We combined eleven metrics into an overall score and tested the algorithms in three simulated microcirculation datasets, and in angiography datasets of the brain of a live rat after craniotomy, an excised rat kidney and a mammary tumour in a live mouse. The algorithms, metrics and datasets, which we have made openly available at https://github.com/AChavignon/PALA and https://doi.org/10.5281/zenodo.4343435 , will facilitate the identification or generation of optimal microbubble-localization algorithms for specific applications.

Synergistic enhancements of ultrasound image contrast with a combination of phase aberration correction and dual apodization with cross-correlation

Dual apodization with cross-correlation (DAX) is a novel adaptive beamforming technique which utilizes two distinct apodization functions in suppressing side lobes and clutter. Previous studies have shown that the performance of DAX in minimizing the effects of phase aberration diminishes with increasing aberrator strength. To achieve greater improvement in image contrast, we propose, in this paper, to combine DAX with a phase aberration correction algorithm based on nearest-neighbor cross-correlation (NNCC). Our simulation and experimental results presented in this work showed that the proposed method allows for synergistic enhancements of image contrast and achieves greater improvement in image quality than using DAX alone or phase aberration correction alone in the presence of weak and strong aberrators. Compared with standard delay-and-sum (DAS) beamforming, using the proposed method on simulated data with weak and strong aberrations increased the contrast-to-noise ratio (CNR) values from 4.10 to 10.96 and from 1.69 to 9.80, respectively. Experimental results were obtained using pork tissues of 4 and 10 mm thickness and a tissue-mimicking phantom. The CNR values increased from 3.74 to 9.72 for the 4-mm pork aberrator and from 1.27 to 8.17 for the 10-mm pork aberrator.

Speckle reduction in ultrasonic images through a maximum likelihood based adaptive filter

Speckle poses serious problems in the interpretation of ultrasound images. It reduces contrast and resolution, making it difficult to identify the presence of abnormalities in B mode images. Using a recently proposed compound probability density function (pdf) for the statistics of the backscattered ultrasonic signals, an adaptive filter for speckle reduction is implemented and tested on B mode images of a tissue mimicking phantom. Results suggest that the adaptive filter based on a maximum likelihood approach improves the ability to classify targets in images while retaining the details in the original unprocessed image.

Segmentation of abdominal ultrasound images of the prostate using a priori information and an adapted noise filter

This article discusses a method for the automatic segmentation of trans-abdominal ultrasound images of the prostate. Segmentation begins with the application of a filter to enhance the contours without modifying the image information. It combines adaptive morphological filtering and median filtering to detect the noise-containing regions and smooth them. A heuristic optimization algorithm searches for the contour initialized from a prostate model. The performance of the algorithm was tested by comparing the resulting contours with those obtained by manual segmentation. The average distance between the contours was 2.5 mm and the average coverage index was 93%.

Polarization Effects in Optical Coherence Tomography of Various Biological Tissues

Polarization sensitive optical coherence tomography (PS-OCT) was used to obtain spatially resolved ex vivo images of polarization changes in skeletal muscle, bone, skin and brain. Through coherent detection of two orthogonal polarization states of the signal formed by interference of light reflected from the biological sample and a mirror in the reference arm of a Michelson interferometer, the depth resolved change in polarization was measured. Inasmuch as any fibrous structure will influence the polarization of light, PS-OCT is a potentially powerful technique investigating tissue structural properties. In addition, the effects of single polarization state detection on OCT image formation is demonstrated.

Phase-domain processing of optical coherence tomography images

In optical coherence tomography (OCT), images are usually formed from the envelope of the measured interference signal. Computation of the absolute magnitude of the signal for measurement of the envelope is a nonlinear process that destroys phase information. This study explores the idea of recording and processing the phase of the OCT interference signal before calculation of the magnitudes for display. Processing the partially coherent OCT signals in the complex domain provides the opportunity to correct phase aberrations responsible for speckle noise in OCT images. We describe an OCT system that incorporates a quadrature-demodulation scheme for accurate recording of the phase and amplitude of OCT signals from single or multiple detectors. A speckle-reduction technique that works in the complex domain, called the zero-adjustment procedure (ZAP), is investigated as an example of complex-domain processing. After demonstrating its speckle-correction properties mathematically and in numerical simulations, we apply ZAP to OCT images of living skin. The results show that ZAP reduces speckle contrast in regions where scatterer density is high and expands the range of gray values in the image. However, as presently implemented, ZAP tends to blur sharp boundaries between image features. © 1999 Society of Photo-Optical Instrumentation Engineers.

Array detection for speckle reduction in optical coherence microscopy

This paper introduces a spatial-diversity method for speckle suppression in optical coherence microscopy. The method is based on combining interference signals from an array of detectors placed in the back focal plane of the objective lens, such that elements receive light backscattered from the sample volume at different angles. Incoherently adding ('compounding') the signals increases the signal-to-noise ratio of the processed image compared to that attainable with a single detector. The speckle-reduction method was demonstrated with a benchtop microscope equipped with a quadrant photodiode. To evaluate its potential application in dermatology, images of living skin acquired with and without compounding were compared. The quality of the compounded images was found to be substantially better. A signal-to-noise gain close to a factor of two (the theoretical maximum attainable using four detectors) was achieved without a significant loss in resolution. The method can be applied to arrays with a larger number of elements, potentially enabling more advanced forms of spatial-diversity and adaptive-optics methods.