Biological soft tissues are functional agglomerates of cells. They constitute the microenvironment where intercellular communication occurs. In turn, their woven structure underlies mechanical properties that contribute to their roles in the context of the organs and the organisms that contain them. Therefore, determining the density and spatial distribution of cells within the tissue offers key information for understanding its physiological properties and its state. X-ray holographic nanotomography is a non-destructive imaging technique capable of resolving subcellular details in biological tissues that has shown promising advantages to study the structure of neuronal circuits. However, the dimensions of the datasets required – covering volume landscapes of ~mm3 – make manual annotation of individual nuclei an unrealistic task. We developed and trained an automated image segmentation classifier that accurately detects and segments cell nuclei in mouse brain tissue imaged with x-ray holographic nanotomography, and that generalises to similar datasets obtained from biological replicates with minimal additional ground truth. It provides the spatial locations and morphologies of the ~80k nuclei per dataset with a high recall. It harnesses the strengths of a high-performance computing cluster and embeds the curated results in two main simplified outcomes: a data table and explorable image segmentations and meshes associated with the original dataset, in a browser-compatible format that simplifies proofreading by multiple users. The classifier we present here can be readily integrated into an automated analytical pipeline for histological datasets obtained with synchrotron x-ray holographic nanotomography in the context of systems neuroscience as well as broader tissue life science studies.
Enabling exploration of biological tissue in three-dimensions at sub-cellular scale is instrumental for advancing our understanding of biological systems and for finding better ways to cope with diseases. Over the last few years, remarkable advances in microscopy facilitated probing cells and tissues at the nanometer scale but many limitations are yet to be overcome. Here we present a novel technique which enables label-free volume imaging of biological tissue with pixel sizes down to 25 nm while maintaining extensive sample coverage. X-ray holographic nanotomography is a full-field 3D imaging technique which benefits from the deep penetration of X-rays and the powerful mechanism of phase contrast. By using cryogenic sample preservation, the tissue can be investigated close to the native state. The unprecedented data created by this technique opens new avenues in life sciences research.
Bone properties at all length scales have a major impact on the fracture risk in disease such as osteoporosis. However, quantitative 3D data on bone tissue at the cellular scale are still rare. Here we propose to use magnified X-ray phase nano-CT to quantify bone ultra-structure in human bone, on the new setup developed on the beamline ID16A at the ESRF, Grenoble. Obtaining 3D images requires the application of phase retrieval prior to tomographic reconstruction. Phase retrieval is an ill-posed problem for which various approaches have been developed. Since image quality has a strong impact on the further quantification of bone tissue, our aim here is to evaluate different phase retrieval methods for imaging bone samples at the cellular scale. Samples from femurs of female donors were scanned using magnified phase nano-CT at voxel sizes of 120 and 30 nm with an energy of 33 keV. Four CT scans at varying sample-to-detector distances were acquired for each sample. We evaluated three phase retrieval methods adapted to these conditions: Paganin’s method at single distance, Paganin’s method extended to multiple distances, and the contrast transfer function (CTF) approach for pure phase objects. These methods were used as initialization to an iterative refinement step. Our results based on visual and quantitative assessment show that the use of several distances (as opposed to single one) clearly improves image quality and the two multi-distance phase retrieval methods give similar results. First results on the segmentation of osteocyte lacunae and canaliculi from such images are presented.
In high-resolution tomography, one needs high-resolved projections in order to reconstruct a high-quality 3D map of a sample. X-ray ptychography is a robust technique which can provide such high-resolution 2D projections taking advantage of coherent X-rays. This technique was used in the far-field regime for a fair amount of time, but it can now also be implemented in the near-field regime. In both regimes, the technique enables not only high-resolution imaging, but also high sensitivity to the electron density of the sample. The combination with tomography makes 3D imaging possible via ptychographic X-ray computed tomography (PXCT), which can provide a 3D map of the complex-valued refractive index of the sample. The extension of PXCT to X-ray energies above 15 keV is challenging, but it can allow the imaging of object opaque to lower energy. We present here the implementation and developments of high-energy near- and far-field PXCT at the ESRF.
Brain tissues have been an attractive subject for investigations in neuropathology, neuroscience, and neurobiol- ogy. Nevertheless, existing imaging methodologies have intrinsic limitations in three-dimensional (3D) label-free visualisation of extended tissue samples down to (sub)cellular level. For a long time, these morphological features were visualised by electron or light microscopies. In addition to being time-consuming, microscopic investigation includes specimen fixation, embedding, sectioning, staining, and imaging with the associated artefacts. More- over, optical microscopy remains hampered by a fundamental limit in the spatial resolution that is imposed by the diffraction of visible light wavefront. In contrast, various tomography approaches do not require a complex specimen preparation and can now reach a true (sub)cellular resolution. Even laboratory-based micro computed tomography in the absorption-contrast mode of formalin-fixed paraffin-embedded (FFPE) human cerebellum yields an image contrast comparable to conventional histological sections. Data of a superior image quality was obtained by means of synchrotron radiation-based single-distance X-ray phase-contrast tomography enabling the visualisation of non-stained Purkinje cells down to the subcellular level and automated cell counting. The question arises, whether the data quality of the hard X-ray tomography can be superior to optical microscopy. Herein, we discuss the label-free investigation of the human brain ultramorphology be means of synchrotron radiation-based hard X-ray magnified phase-contrast in-line tomography at the nano-imaging beamline ID16A (ESRF, Grenoble, France). As an example, we present images of FFPE human cerebellum block. Hard X-ray tomography can provide detailed information on human tissues in health and disease with a spatial resolution below the optical limit, improving understanding of the neuro-degenerative diseases.
The ID16A beamline at ESRF offers unique capabilities for X-ray nano-imaging, and currently produces the worlds brightest high energy diffraction-limited nanofocus. Such a nanoprobe was designed for quantitative characterization of the morphology and the elemental composition of specimens at both room and cryogenic temperatures. Billions of photons per second can be delivered in a diffraction-limited focus spot size down to 13 nm. Coherent X-ray imaging techniques, as magnified holographic-tomography and ptychographic-tomography, are implemented as well as X-ray fluorescence nanoscopy. We will show the latest developments in coherent and spectroscopic X-ray nanoimaging implemented at the ID16A beamline
During the last decade, X-ray micro Computerized Tomography (CT) has become a conventional technique for the three-dimensional (3D) investigation of trabecular bone micro-architecture. Coupling micro-CT to synchrotron sources possesses significant advantages in terms of image quality and gives access to information on bone mineralization which is an important factor of bone quality. We present an overview of the investigation of bone using Synchrotron Radiation (SR) CT from the micro to the nano scale. We introduce two synchrotron CT systems developed at the ESRF based on SR parallel-beam micro-CT and magnified phase CT respectively, achieving down to submicrometric and nanometric spatial resolution. In the latter, by using phase retrieval prior to tomographic reconstruction, the system provides maps of the 3D refractive index distribution. Parallel-beam SR micro-CT has extensively been used for the analysis of trabecular or cortical bone in human or small animals with spatial resolution in the range [3-10] μm. However, the characterization of the bone properties at the cellular scale is also of major interest. At the micrometric scale, the shape, density and morphology of osteocyte lacunae can be studied on statistically representative volumes. At the nanometric scale, unprecedented 3D displays of the canaliculi network have been obtained on fields of views including a large number of interconnected osteocyte lacunae. Finally SR magnified phase CT provides a detailed analysis of the lacuno-canalicular network and in addition information on the organization of the collagen fibers. These findings open new perspectives for three-dimensional quantitative assessment of bone tissue at the cellular scale.
We address the issue of producing automatic video abstracts in the context of the video indexing of animated movies. For a quick browse of a movie's visual content, we propose a storyboard-like summary, which follows the movie's events by retaining one key frame for each specific scene. To capture the shot's visual activity, we use histograms of cumulative interframe distances, and the key frames are selected according to the distribution of the histogram's modes. For a preview of the movie's exciting action parts, we propose a trailer-like video highlight, whose aim is to show only the most interesting parts of the movie. Our method is based on a relatively standard approach, i.e., highlighting action through the analysis of the movie's rhythm and visual activity information. To suit every type of movie content, including predominantly static movies or movies without exciting parts, the concept of action depends on the movie's average rhythm. The efficiency of our approach is confirmed through several end-user studies.
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