Mesoscopic three-dimensional hard X-ray imaging of central and peripheral nervous system

Micro computed tomography (μCT), either by means of hard X rays from synchrotronradiation (SR) facilities, or from advanced laboratory sources, has been proven as a powerful method for the nondestructive three-dimensional visualization of biological specimens with isotropic micro- and even nanometer resolution. The established absorption-contrast modality of μCT has been sometimes associated with the need for contrast agents, whereas the more advanced phase-contrast modality has yielded superior results for biological specimens without staining. For around three decades, phase-contrast μCT has been considered between a hundred and a thousand times better than absorption-contrast μCT, based on the ratio of the imaginary and the real part of the complex refractive index that could be determined using the two modalities at desired photon energies. The results of the present study elucidate that for formalin-fixed, paraffin-embedded nervous tissues, conventional μCT delivers a much better contrast than originally expected. Related measurements were performed at a SR facility using monochromatic X rays. The photon energies were not equal for absorption- and phase-contrast measurements, but selected to obtain optimized contrast within a reasonable period of time. The choice of the photon energy, which is much smaller for absorption-contrast μCT, explains that the contrast difference between phase- and absorption-contrast μCT, indicated by the contrast-to-noise ratio of anatomical regions in the respective datasets being about two times better for phase μCT, is much smaller than reported in literature. It should be highlighted that μCT in absorption- and phase contrast are complementary methods and a combination might give additional quantitative insights into the three-dimensional images. For example, one can register the data and build a joint histogram from the common volume to segment anatomical features indistinguishable using just one imaging modality. The main relevance of such results lies in the opportunity to employ laboratory-based μCT, which are much better accessible and cost-effective than μCT at SR facilities. This approach was benchmarked on peripheral nerve reconstruction. The threedimensional visualization of regenerating nerves inside collagen scaffolds was feasible and included the automatic extraction of anatomical features to quantify the regeneration. Indeed, the characteristic parameters, revealed from the conventional μCT data, were significantly different between regenerating and control nerves. The approach including specimen preparation, data acquisition, and analysis has been useful for the investigations of the anatomical alterations in medial temporal epilepsy and the time-critical diagnosis of vasculitis prior to the standard histology

Automatic deformable registration of histological slides to {μCT} volume {3D}-Data

Localizing a histological section in the three‐dimensional dataset of a different imaging modality is a challenging 2D‐3D registration problem. In the literature, several approaches have been proposed to solve this problem; however, they cannot be considered as fully automatic. Recently, we developed an automatic algorithm that could successfully find the position of a histological section in a micro computed tomography (μCT) volume. For the majority of the datasets, the result of localization corresponded to the manual results. However, for some datasets, the matching μCT slice was off the ground‐truth position. Furthermore, elastic distortions, due to histological preparation, could not be accounted for in this framework. In the current study, we introduce two optimization frameworks based on normalized mutual information, which enabled us to accurately register histology slides to volume data. The rigid approach allocated 81 % of histological sections with a median position error of 8.4 μm in jaw bone datasets, and the deformable approach improved registration by 33 μm with respect to the median distance error for four histological slides in the cerebellum dataset

Automatic histology registration in application to X-ray modalities

Registration of microscope images to Computed Tomography (CT) 3D volumes is a challenging task because it requires not only multi-modal similarity measure but also 2D-3D or slice-to-volume correspondence. This type of registration is usually done manually which is very time-consuming and prone to errors. Recently we have developed the first automatic approach to localize histological sections in μCT data of a jaw bone. The median distance between the automatically found slices and the ground truth was below 35 μm. Here we explore the limitations of the method by applying it to three tomography datasets acquired with grating interferometry, laboratory-based μCT and single-distance phase retrieval. Moreover, we compare the performance of three feature detectors in the proposed framework, i.e. Speeded Up Robust Features (SURF), Scale Invariant Feature Transform (SIFT) and Affine SIFT (ASIFT). Our results show that all the feature detectors performed significantly better on the grating interferometry dataset than on other modalities. The median accuracy for the vertical position was 0.06 mm. Across the feature detector types the smallest error was achieved by the SURF-based feature detector (0.29 mm). Furthermore, the SURF-based method was computationally the most efficient. Thus, we recommend to use the SURF feature detector for the proposed framework

Three-dimensional and non-destructive characterization of nerves inside conduits using laboratory-based micro computed tomography

Histological assessment of peripheral nerve regeneration in animals is tedious, time-consuming and challenging for three-dimensional analysis

Three-dimensional imaging and analysis of entire peripheral nerves after repair and reconstruction

We wanted to achieve a three-dimensional (3D), non-destructive imaging and automatic post-analysis and evaluation of reconstructed peripheral nerves without involving cutting and staining processes

Conference Proceedings: Removing ring artefacts from synchrotron radiation-based hard x-ray tomography data

In hard X-ray microtomography, ring artefacts regularly originate from improperly functioning pixel elements on the detector or from particles and scratches on the scintillator. We show that due to the high sensitivity of contemporary beamline setups further causes inducing inhomogeneities in the impinging wavefronts have to be considered. We propose in this study a method to correct the thereby induced failure of simple flatfield approaches. The main steps of the pipeline are (i) registration of the reference images with the radiographs (projections), (ii) integration of the flat-field corrected projection over the acquisition angle, (iii) high-pass filtering of the integrated projection, (iv) subtraction of filtered data from the flat-field corrected projections. The performance of the protocol is tested on data sets acquired at the beamline ID19 at ESRF using single distance phase tomography