This paper presents a methodology and related experimental results as a first attempt to answer the question of anuran audition and their ability to localize sound at acoustic frequencies they should not. An achiral digital holographic interferometer is designed so as to simultaneously measure the left and right tympanic vibrations on living specimen. The tympanic membranes are excited by an acoustic antenna including 22 loudspeakers emitting sound in the frequency range 1000 Hz to 3000 Hz. The first experimental results are presented.
X-ray propagation-based phase contrast imaging (XPCI) relies on the coherence of the X-ray beam to achieve contrast from phase shift by letting the beam propagate in free space, hence yielding a Fresnel or Fraunhofer diffraction pattern. This contrast regime arises in high resolution imaging, where it is used for tomography in a wide range of applications. The exploitation of such images requires a phase retrieval step, which has proven sensitive to noise in low spatial frequencies. It is thought that incoherent scattering in the sample might contribute to this noise. Therefore, several approaches to combine phase contrast and incoherent scattering have recently been proposed. To this aim, we propose a new way to simulate phase contrast based on the Wigner Distribution Function (WDF). In this framework, the exit wave of the sample is calculated through ray-tracing, which would allow accounting for effects including refraction and reflection. The interference is then calculated in the exit plane using the WDF, instead of in the detector plane, as is the case using classical methods. Images can then be simulated photon by photon, by first simulating incoherent scattering in the sample using a Monte Carlo particle transport code, followed by diffraction by probability sampling of the WDF. As a first demonstration of the framework, we simulate the double-slit experiment, as well as a variant with a scatterer in one of the slits. Since the double-slit has an analytical solution for the WDF, both in its standard form and with different amplitudes in each slit, this enables us to bypass the most challenging numerical difficulties for this initial demonstration.
Spondyloarthritis is an inflammatory rheumatic disease characterized by inflammation of the bone and soft tissues, such as enthesis and synovial membrane, in the spine and peripheral joint. Early diagnosis of this disease plays an important role in deciding the possible treatments but has remained a challenge for decades. Several imaging modalities exist, such as X-ray radiography, Magnetic Resonance Imaging (MRI), and Computed Tomography (CT). However, they are not suitable for the early diagnostics of Spondyloarthritis because of their inability to depict active inflammations. This paper demonstrates the application of a novel X-ray phase contrast imaging (PCI) technique that allows imaging of weakly absorbing tissues with better sensitivities than other conventional imaging modalities. A PCI imaging procedure involving 6 affected (SKG induced) and 6 control mice ankles was carried out at the European Synchrotron (ESRF). Results from the high-resolution X-ray phase contrast tomography performed on the mice’s ankles are presented. It was observed that the improved contrast of the soft tissues could allow us to visualize the inflammations in the form of swelling of the synovial membrane. Deep learning techniques are used to segment and evaluate inflammations. The results obtained in this work highlight the ability of the PCI technique to detect inflammations more efficiently than the other conventionally existing modalities.
X-ray phase contrast imaging has been proven to have a great interest for the diagnosis and the study of many different pathologies, especially for osteoarticular diseases as it allows to visualize every kind of tissue of the joint within a single image. For the time being, phase contrast tomography has been reserved to synchrotrons and its clinical transfer has therefore become a major challenge in the past decades. Different phase contrast imaging techniques are currently studied for that purpose: Grating interferometry, edge illumination and more recently speckle-based imaging. Because of its simplicity, in this work we study the possibility of transferring speckle-based imaging on conventional x-ray sources. The main challenges we have to face are the loss of spatial and temporal coherence of the conventional sources and the loss in resolution when compared to synchrotrons. We present here a numerical simulation code that we can use to study the influence of different experimental parameters. We also introduce a new phase retrieval algorithm for low coherence systems and compare it to already existing ones, showing that it is already performs well, even for conventional sources.
Synchrotron X-ray multi-spectral imaging is a novel imaging modality that may allow tracking cells at high resolution in small animal models. The data volume generated by such technique can be of hundreds of Gigabytes for one animal. Automatic, robust and rapid pipeline is therefore of paramount importance for large-scale studies. The goal of this article is to present a full image analysis pipeline ranging from the CT reconstruction up to the segmentation of nanoparticleslabeled- cells. Experimentally, rats that had received an intracerebral transplantation of gold nanoparticles-labeled cells were imaged in vivo in phase contrast mode (propagation-based imaging technique) at two different energies strategically chosen around the k-edge of gold. We apply a dedicated phase retrieval technique on each projection (out of 2000 for complete 2π rotation) before CT reconstruction. Then, a rigid registration is performed between the images below and above k-edge for accurate subtraction of the two data sets, leading to gold concentration maps. Due to the large number of specimens, the registration is based on the automatic segmentation of the cranial skull. Finally, an automatic segmentation of gold-labeled cells within the brain is performed based on high spots of gold concentrations. An example of an in-vivo data set for stroke cell therapy is presented.
Standard histopathological examination is the gold standard for many disease diagnoses although the technique is limited with no full 3D volume analysis possible. Three dimensional X-ray Phase-Contrast Imaging(PCI) methods have been under constant and fast developments in the recent decades due to their superior performance for imaging low density objects and their ability to provide complementary information compared to attenuation based imaging. Despite the progresses, X-ray Phase Contrast Tomography still encounters remaining challenges to overcome on its way to become a routine non-invasive technique allowing the 3D assessment of tissue architecture in laboratory set-ups. Speckle Based Imaging (SBI) forms a new class of X-ray PCI techniques, sensitive to the first derivative of the phase. The set-up involved and the simplicity of implementation provide many advantages to SBI such as having no field of view and no resolution limitation in addition to have low requirements on the beam coherences. These advantages make SBI a good candidate for the transfer on conventional sources. In this work, we present preliminary results obtained on a conventional μCT and their comparison with data acquired at the European Synchrotron. We used a new phase retrieval algorithm based on optical energy conservation. We applied the method on both phantoms and biological samples in order to evaluate its quantitativeness for a transfer. A comparison to previously available speckle tracking algorithms is also performed. We demonstrate that the combination of the phase retrieval method with a standard μCT can achieve high resolution and high contrast within a few minutes, with a comparable image quality to the results obtained using synchrotron light.
Bone micro architecture is believed to play a key role in determining bone quality. We propose a new method
of segmentation based on local shape classification. Bones samples are thus described into their basic elements
(rods and plates). On each bone voxel we calculate the inertia moment of a neighborhood obtained by local
geodesic dilation in the bone volume. The dilated volume is obtained through a homothopic dilation using the
Fast Marching algorithms. The size of the dilated volume is choosen from local aperture diameter in order to
be scale independent. The bone cross-section is calculated using an optimized granulometry algorithm. The
segmentation has been carried on a wide range of human trabecular bone with varied structure. Voxels are then
classified according the ratio between the inertia moments of the dilated volumes.
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