A 2-D anatomic breast ductal computer phantom for ultrasonic imaging

International audienceMost breast cancers (85%) originate from the epithelium and develop first in the ductolobular structures. In screening procedures, the mammary epithelium should therefore be investigated first by performing of an anatomically guided examination. For this purpose (mass screening, surgical guidance), we developed a two-dimensional anatomic phantom corresponding to an axial cross-section of the ductolobular structures, which makes it possible to better understand the interactions between the breast composition and ultrasound. The various constitutive tissues were modeled as a random inhomogeneous continuum with density and sound speed fluctuations. Ultrasonic pulse propagation through the breast computer phantom was simulated using a finite element time domain method (the phantom can be used with other propagation codes). The simulated Ductal Echographic image is compared with the Ductal Tomographic (DT) reconstruction. The preliminary results obtained show that the DT method is more satisfactory in terms of both the contrast and the resolution

New methods for deep tissue imaging

Microscopes play vital role biological science and medicine. For single photon microscopies, the scattering of photons makes regions of interest located a few hundred microns beneath the surface inaccessible. Multi-photon microscopes are widely used for minimally invasive in vivo brain imaging due to their increased imaging depth. However, multi-photon microscopes are hampered by limited dynamic range, preventing weak sample features from being detected in the presence of strong features, or preventing the capture of unpredictable bursts in sample strength. In the first part of the thesis, I present a solution to vastly improve the dynamic range of a multi-photon microscope while limiting potential photodamage. Benefits are shown in both structural and in-vivo functional mouse brain imaging applications. In the second section of the thesis work, I explore a completely different approach towards deep tissue imaging by changing the type of radiation from light to ultrasound. Inspired by an optical phase contrast technique invented in the lab, I developed an unprecedented ultrasound imaging system that can visualize the ultrasound phase contrast in the sample. The ultrasound phase contrast technique is able to visualize local sound speed variations instead of local reflectivity. Compared with existing sound speed tomography systems, our technique eliminates the cumbersome sound speed reconstruction process. The research work in this section contains three parts. In the first part, we designed a low-cost single element scanning system as proof of concept. In the second part, we implemented the ultrasound phase contrast imaging system on a commercial linear phased transducer array and an imaging apparatus designed for samples with finite thickness. In the third part, we studied the feasibility of ultrasound phase contrast imaging in arbitrarily thick tissue. We presented a complete workflow of theoretical study, simulation, prototyping and experimental testing for all three parts.2020-02-28T00:00:00

End-to-end Cardiac Ultrasound Simulation for a Better Understanding of Image Quality

International audienceUltrasound imaging is a very versatile and fast medical imag-ing modality, however it can suffer from serious image quality degrada-tion. The origin of such loss of image quality is often difficult to identifyin detail, therefore it makes it difficult to design probes and tools thatare less impacted. The objective of this manuscript is to present an end-to-end simulation pipeline that makes it possible to generate syntheticultrasound images while controlling every step of the pipeline, from thesimulated cardiac function, to the torso anatomy, probe parameters, andreconstruction process. Such a pipeline enables to vary every parameterin order to quantitatively evaluate its impact on the final image quality.We present here first results on classical ultrasound phantoms and a dig-ital heart. The utility of this pipeline is exemplified with the impact ofribs on the resulting cardiac ultrasound image

Anisotropic Diffusion Filter with Memory based on Speckle Statistics for Ultrasound Images

Ultrasound imaging exhibits considerable difficulties for medical visual inspection and for the development of automatic analysis methods due to speckle, which negatively affects the perception of tissue boundaries and the performance of automatic segmentation methods. With the aim of alleviating the effect of speckle, many filtering techniques are usually considered as a preprocessing step prior to automatic analysis methods or visual inspection. Most of the state-of-the-art filters try to reduce the speckle effect without considering its relevance for the characterization of tissue nature. However, the speckle phenomenon is the inherent response of echo signals in tissues and can provide important features for clinical purposes. This loss of information is even magnified due to the iterative process of some speckle filters, e.g., diffusion filters, which tend to produce over-filtering because of the progressive loss of relevant information for diagnostic purposes during the diffusion process. In this work, we propose an anisotropic diffusion filter with a probabilistic-driven memory mechanism to overcome the over-filtering problem by following a tissue selective philosophy. Specifically, we formulate the memory mechanism as a delay differential equation for the diffusion tensor whose behavior depends on the statistics of the tissues, by accelerating the diffusion process in meaningless regions and including the memory effect in regions where relevant details should be preserved. Results both in synthetic and real US images support the inclusion of the probabilistic memory mechanism for maintaining clinical relevant structures, which are removed by the state-of-the-art filters

Minimum Variance Approaches to Ultrasound Pixel-Based Beamforming.

We analyze the principles underlying minimum variance distortionless response (MVDR) beamforming in order to integrate it into a pixel-based algorithm. There is a challenge posed by the low echo signal-to-noise ratio (eSNR) when calculating beamformer contributions at pixels far away from the beam centreline. Together with the well-known scarcity of samples for covariance matrix estimation, this reduces the beamformer performance and degrades the image quality. To address this challenge, we implement the MVDR algorithm in two different ways. First, we develop the conventional minimum variance pixel-based (MVPB) beamformer that performs the MVDR after the pixel-based superposition step. This involves a combination of methods in the literature, extended over multiple transmits to increase the eSNR. Then we propose the coherent MVPB beamformer, where the MVDR is applied to data within individual transmits. Based on pressure field analysis, we develop new algorithms to improve the data alignment and matrix estimation, and hence overcome the low-eSNR issue. The methods are demonstrated on data acquired with an ultrasound open platform. The results show the coherent MVPB beamformer substantially outperforms the conventional MVPB in a series of experiments, including phantom and in vivo studies. Compared to the unified pixel-based beamformer, the newest delay-and-sum algorithm in [1], the coherent MVPB performs well on regions that conform to the diffuse scattering assumptions on which the minimum variance principles are based. It produces less good results for parts of the image that are dominated by specular reflections

Detection and imaging in a random medium: A matrix method to overcome multiple scattering and aberration

We present an imaging technique particularly suited to the detection of a target embedded in a strongly scattering medium. Classical imaging techniques based on the Born approximation fail in this kind of configuration because of multiply scattered echoes and aberration distortions. The experimental set up we consider uses an array of programmable transmitters/receivers. A target is placed behind a scattering medium. The impulse responses between all array elements are measured and form a matrix. The core of the method is to separate the single-scattered echo of the target from the multiple scattering background. This is possible because of a deterministic coherence along the antidiagonals of the array response matrix, which is typical of single scattering. Once this operation is performed, target detection is achieved by applying the DORT method (French acronym for decomposition of the time reversal operator). Experimental results are presented in the case of wide-band ultrasonic waves around 3 MHz. A 125-element array is placed in front of a collection of randomly distributed steel rods (diameter 0.8mm). The slab thickness is three times the scattering mean free path. The target is a larger steel cylinder (diameter 15 mm) that we try to detect and localize. The quality of detection is assessed theoretically based on random matrix theory and is shown to be significantly better than what is obtained with classical imaging methods. Aside from multiple scattering, the technique is also shown to reduce the aberrations induced by an heterogeneous layer.Comment: 48 pages, 18 figures, corrected typos, v