Regularized phase tomography enables study of mineralized and unmineralized tissue in porous bone scaffold

Regularized phase tomography was used to image non‐calcified fibrous matrix in in vitro cell‐cultivated porous bone scaffold samples. 3D micro‐architecture of bone and bone scaffold has previously been studied by micro‐computed tomography, synchrotron radiation (SR) micro‐computed tomography and microdiffraction. However, neither of these techniques can resolve the low‐calcified immature pre‐bone fibrous structures. Skelite porous scaffold discs were seeded with osteoblasts, a combination of osteoblast and pre‐osteoclasts and, as controls, with pre‐osteoclasts only, and then cultivated for 8 weeks. They were subsequently imaged using SR propagation‐based phase contrast imaging. Reconstructions using a regularized holographic phase tomography approach were compared to standard (absorption) SR micro‐computed tomography, which show that quantitative analysis, such as volume and thickness measurements, of both the calcified fraction and the immature bone matrix in the reconstructed volumes is enabled. Indications of the effect of this type of culture on Skelite, such as change in mineralization and deposit of mature bone on the walls of the scaffold, are found. The results are verified with a histological study.     

Development of a contrast‐enhanced micro computed tomography protocol for the oval squid (Sepioteuthis lessoniana) brain

Coleoid cephalopods (squid, cuttlefish, and octopus) have a well‐developed and complex central nervous system. Its absolute size is the largest among invertebrates, and the brain‐to‐body mass ratio is larger than that of fish and reptiles and equivalent to that of birds and mammals. Although a number of histological studies have been conducted on the brains of cephalopods, most of them used a light microscope or an electron microscope, which show the microstructure of the brain, but often cannot image the whole brain instantaneously. Of late, micro computed tomography (CT) has gained popularity for imaging animal brains because it allows for noninvasive three‐dimensional (3D) reconstruction and preprocessing that are not cumbersome. To perform micro‐CT on cephalopod brains, we first tested conditions suitable for preprocessing, paying special attention to staining conditions that would provide high contrast images. Four agents, iodine in 99.5% ethanol, iodine potassium iodide in water (IKI), phosphotungstic acid in 70% ethanol, and nonionic iodinated contrast agent in water, were tested at various concentrations and durations on brain of juvenile oval squid. To evaluate the quality of staining, we calculated the contrast ratio of the two‐dimensional (2D) images and compared 3D segmentation of the best and worst 2D images. We concluded that 3% IKI staining for 7 days was the best combination to enhance the images contrast of the oval squid brain, in which each brain lobe was clearly detected and 3D segmentation of the whole brain was possible. The wider applicability of this preprocessing method for micro‐CT of the brains of other cephalopods is discussed.     

A method for the evaluation of thousands of automated 3D stem cell segmentations

There is no segmentation method that performs perfectly with any dataset in comparison to human segmentation. Evaluation procedures for segmentation algorithms become critical for their selection. The problems associated with segmentation performance evaluations and visual verification of segmentation results are exaggerated when dealing with thousands of three‐dimensional (3D) image volumes because of the amount of computation and manual inputs needed. We address the problem of evaluating 3D segmentation performance when segmentation is applied to thousands of confocal microscopy images (z‐stacks). Our approach is to incorporate experimental imaging and geometrical criteria, and map them into computationally efficient segmentation algorithms that can be applied to a very large number of z‐stacks. This is an alternative approach to considering existing segmentation methods and evaluating most state‐of‐the‐art algorithms. We designed a methodology for 3D segmentation performance characterization that consists of design, evaluation and verification steps. The characterization integrates manual inputs from projected surrogate ‘ground truth’ of statistically representative samples and from visual inspection into the evaluation. The novelty of the methodology lies in (1) designing candidate segmentation algorithms by mapping imaging and geometrical criteria into algorithmic steps, and constructing plausible segmentation algorithms with respect to the order of algorithmic steps and their parameters, (2) evaluating segmentation accuracy using samples drawn from probability distribution estimates of candidate segmentations and (3) minimizing human labour needed to create surrogate ‘truth’ by approximating z‐stack segmentations with 2D contours from three orthogonal z‐stack projections and by developing visual verification tools. We demonstrate the methodology by applying it to a dataset of 1253 mesenchymal stem cells. The cells reside on 10 different types of biomaterial scaffolds, and are stained for actin and nucleus yielding 128 460 image frames (on average, 125 cells/scaffold × 10 scaffold types × 2 stains × 51 frames/cell). After constructing and evaluating six candidates of 3D segmentation algorithms, the most accurate 3D segmentation algorithm achieved an average precision of 0.82 and an accuracy of 0.84 as measured by the Dice similarity index where values greater than 0.7 indicate a good spatial overlap. A probability of segmentation success was 0.85 based on visual verification, and a computation time was 42.3 h to process all z‐stacks. While the most accurate segmentation technique was 4.2 times slower than the second most accurate algorithm, it consumed on average 9.65 times less memory per z‐stack segmentation.     

The effect of X‐ray micro computed tomography image resolution on flow properties of porous rocks

The study of digital rock physics has seen significant advances due to the development of X‐ray micro computed tomography scanning devices. One of the advantages of using such a device is that the pore structure of rock can be mapped down to the micrometre level in three dimensions. However, in providing such high‐resolution images (low voxel size), the resulting file sizes are necessarily large (of the order of gigabytes). Lower image resolution (high voxel size) produces smaller file sizes (of the order of hundreds of megabytes), but risks losing significant details. This study describes the effect of the image resolution obtained by means of hardware‐based and software‐based approach. Four samples of porous rock were scanned using a SkyScan 1173 High Energy Micro‐CT. We found that acquisition using increased pixel binning of the camera (hardware‐based resizing) significantly affects the calculated physical properties of the samples. By contrast, voxel resizing by means of a software‐based approach during the reconstruction process yielded less effect on the porosity and specific surface area of the samples. However, the decreasing resolution of the image obtained by both the hardware‐based and the software‐based approaches affects the permeability significantly. We conclude that simulating fluid flow through the pore space using the Lattice Boltzmann method to calculate the permeability has a significant dependency on the image resolution.     

Micro‐CT versus synchrotron radiation phase contrast imaging of human cochlea

High‐resolution images of the cochlea are used to develop atlases to extract anatomical features from low‐resolution clinical computed tomography (CT) images. We compare visualization and contrast of conventional absorption‐based micro‐CT to synchrotron radiation phase contrast imaging (SR‐PCI) images of whole unstained, nondecalcified human cochleae. Three cadaveric cochleae were imaged using SR‐PCI and micro‐CT. Images were visually compared and contrast‐to‐noise ratios (CNRs) were computed from n = 27 regions‐of‐interest (enclosing soft tissue) for quantitative comparisons. Three‐dimensional (3D) models of cochlear internal structures were constructed from SR‐PCI images using a semiautomatic segmentation method. SR‐PCI images provided superior visualization of soft tissue microstructures over conventional micro‐CT images. CNR improved from 7.5 ± 2.5 in micro‐CT images to 18.0 ± 4.3 in SR‐PCI images (p < 0.0001). The semiautomatic segmentations yielded accurate reconstructions of 3D models of the intracochlear anatomy. The improved visualization, contrast and modelling achieved using SR‐PCI images are very promising for developing atlas‐based segmentation methods for postoperative evaluation of cochlear implant surgery.     

结合先验稀疏字典和空洞填充的CT图像肝脏分割

针对复杂多变的肝脏图像,提出了一种基于先验稀疏字典和空洞填充的三维肝脏图像分割方法。对腹部CT图像进行Gabor特征提取,并分别在Gabor图像和灰度图像的肝脏金标准边界上选择大小相同的图像块作为两组训练集,利用训练集得到两种查询字典及稀疏编码。将金标准图像与待分割图像配准,并将配准后的肝脏边界作为待分割图像的肝脏初始边界;在初始边界点上的十邻域内选择大小相同的两组图像块作为测试样本,利用测试样本与查询字典计算稀疏编码及重构误差,并选择重构误差最小的图像块的中心作为待分割肝脏的边界点;最后,设计一种空洞填充方法对肝脏边界进行补全和平滑处理,得到最终分割结果。利用医学图像计算和计算机辅助介入国际会议中提供的肝脏数据进行了实验验证。结果表明,该方法对肝脏分割图像具有较好的适用性和鲁棒性,并获得了较高的分割精度。其中,平均体积重叠率误差为(5.21±0.45)%,平均相对体积误差为(0.72±0.12)%,平均对称表面距离误差为(0.93±0.14)mm。     

The chord length transform and the segmentation of crossing fibres

Segmentation of crossing fibres is a complex problem of image processing. In the present paper, various solutions are presented basing on tools of morphological image processing. Two new image transforms are introduced – the lineal distance transform and the chord length transform. Both transforms are applied to two‐dimensional images and their results are three‐dimensional images. Thus, the segmentation problem originally formulated for crossing fibres observed in a two‐dimensional image can be reformulated as a segmentation problem in a three‐dimensional image. This can be solved by a segmentation in the three‐dimensional image. Algorithms for the lineal distance transform and the chord length transform are given and their use in image analysis is demonstrated. Furthermore, the chord length distribution function of the foreground of a binary image can efficiently be estimated via the chord length transform.     

Characterization of the three-dimensional structure of a metallic foam during compressive deformation

X‐ray microtomography has been employed to collect three‐dimensional images of aluminium closed‐cell foam, enabling the internal structure to be characterized in three dimensions. An experimental technique and image analysis approach has been developed, and is described, in terms of the labelling of cells and the extraction of quantitative data such as the cell volume and cell compression. An in situ compressive deformation experiment has been performed on a single sample in order to illustrate the approach. The effect of the three‐dimensional cellular structure on the mechanisms of deformation suggests not only the position of large cell volumes to be very important in the local concentration of stress, but also the distribution of cell volumes of immediate neighbours.     

Reconstruction of highly porous structures from FIB‐SEM using a deep neural network trained on synthetic images

Combining scanning electron microscopy with serial slicing by a focused ion beam yields spatial image data of materials structures at the nanometer scale. However, the depth of field of the scanning electron microscopic images causes unwanted effects when highly porous structures are imaged. Proper spatial reconstruction of such porous structures from the stack of microscopic images is a tough and in general yet unsolved segmentation problem. Recently, machine learning methods have proven to yield solutions to a variety of image segmentation problems. However, their use is hindered by the need of large amounts of annotated data in the training phase. Here, we therefore replace annotated real image data by simulated image stacks of synthetic structures – realizations of stochastic germ–grain models and random packings. This strategy yields the annotations for free, but shifts the effort to choosing appropriate stochastic geometry models and generating sufficiently realistic scanning electron microscopic images.     

Morphological segmentation of FIB‐SEM data of highly porous media

Nanoporous materials play an important role in modern batteries as well as fuel cells. The materials microstructure needs to be analyzed as it determines the electrochemical properties. However, the microstructure is too fine to be resolved by microcomputed tomography. The method of choice to analyze the microstructure is focused ion beam nanotomography (FIB‐SEM). However, the reconstruction of the porous 3D microstructure from FIB‐SEM image data in general has been an unsolved problem so far. In this paper, we present a new method using morphological operations. First, features are extracted from the data. Subsequently, these features are combined to an initial segmentation, that is then refined by a constrained watershed transformation. We evaluate our method with synthetic data, generated by a simulation of the FIB‐SEM imaging process. We compare the ground truth in the simulated data to the segmentation result. The new method is found to produce a much smaller error than existing techniques.     

基于Hessian矩阵和熵的CT序列图像裂缝分割方法

工业CT序列图像的各向不同性和伪影会影响裂缝分割精确度和准确度,因此提出一种基于Hessian矩阵和熵的各向不同性工业CT序列图像裂缝自动分割方法。首先,用基于Hessian矩阵的多尺度线状滤波增强裂缝区域,抑制非线状区域;然后,建立一种新的二维直方图,获取滤波之后层内和层间的信息;再根据直方图的最大类熵确定阈值区间,最终得到裂缝的二值化分割结果。实验表明,所提方法不仅能够满足实际工业CT序列图像裂缝分割中精确、自动的分割要求,而且相较其他4种已有方法,能够得到更完整、更准确的分割结果。     

FCM聚类算法和粗糙集在医疗图像分割中的应用

本文通过结合FCM聚类算法和粗糙集，提出了一种新的图像分割方法。首先，以不同聚类数情况下FCM的分割结果为依据构建属性值表，基于属性构成的不可分辨关系将图像分成多个小区域；然后，通过值约简获得各属性权值并以此为依据，计算各区域之间的差异度，进而通过差异度定义的等价关系，实现各区域相似度评价；最后，通过相似度定义的最终等价关系实现区域合并，完成图像分割。该方法在人工生成图像和大脑CT图像及MRI图像的分割中得到验证，实验结果表明，本文方法和FCM方法相比，可以降低错分率，且对模糊边界区域的分割效果较好。     

Three‐dimensional cellular distribution in polymeric scaffolds for bone regeneration: a microCT analysis compared to SEM,CLSM and DNA content

In orthopaedic surgery the tissues damaged by injury or disease could be replaced using constructs based on biocompatible materials, cells and growth factors. Scaffold design, porosity and early colonization are key components for the implant success. From biological point of view, attention may be also given to the number, type and size of seeded cells, as well as the seeding technique and cell morphological and volumetric alterations. This paper describes the use of the microCT approach (to date used principally for mineralized matrix quantification) to observe construct colonization in terms of cell localization, and make a direct comparison of the microtomographic sections with scanning electron microscopy images and confocal laser scanning microscope analysis. Briefly, polycaprolactone scaffolds were seeded at different cell densities with MG63 osteoblastic‐like cells. Two different endpoints, 1 and 2 weeks, were selected for the three‐dimensional colonization and proliferation analysis of the cells. By observing all images obtained, in addition to a more extensive distribution of cells on scaffolds surfaces than in the deeper layers, cell volume increased at 2 weeks compared to 1 week after seeding. Combining the cell number quantification by deoxyribonucleic acid analysis and the single cell volume changes by confocal laser scanning microscope, we validated the microCT segmentation method by finding no statistical differences in the evaluation of the cell volume fraction of the scaffold. Furthermore, the morphological results of this study suggest that an effective scaffold colonization requires a precise balance between different factors, such as number, type and size of seeded cells in addition to scaffold porosity.     

A guide to analysis and reconstruction of serial block face scanning electron microscopy data

Serial block face scanning electron microscopy (SBF‐SEM) is a relatively new technique that allows the acquisition of serially sectioned, imaged and digitally aligned ultrastructural data. There is a wealth of information that can be obtained from the resulting image stacks but this presents a new challenge for researchers – how to computationally analyse and make best use of the large datasets produced. One approach is to reconstruct structures and features of interest in 3D. However, the software programmes can appear overwhelming, time‐consuming and not intuitive for those new to image analysis. There are a limited number of published articles that provide sufficient detail on how to do this type of reconstruction. Therefore, the aim of this paper is to provide a detailed step‐by‐step protocol, accompanied by tutorial videos, for several types of analysis programmes that can be used on raw SBF‐SEM data, although there are more options available than can be covered here. To showcase the programmes, datasets of skeletal muscle from foetal and adult guinea pigs are initially used with procedures subsequently applied to guinea pig cardiac tissue and locust brain. The tissue is processed using the heavy metal protocol developed specifically for SBF‐SEM. Trimmed resin blocks are placed into a Zeiss Sigma SEM incorporating the Gatan 3View and the resulting image stacks are analysed in three different programmes, Fiji, Amira and MIB, using a range of tools available for segmentation. The results from the image analysis comparison show that the analysis tools are often more suited to a particular type of structure. For example, larger structures, such as nuclei and cells, can be segmented using interpolation, which speeds up analysis; single contrast structures, such as the nucleolus, can be segmented using the contrast‐based thresholding tools. Knowing the nature of the tissue and its specific structures (complexity, contrast, if there are distinct membranes, size) will help to determine the best method for reconstruction and thus maximize informative output from valuable tissue.     

Combining intensity, edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections

We present a region‐based segmentation method in which seeds representing both object and background pixels are created by combining morphological filtering of both the original image and the gradient magnitude of the image. The seeds are then used as starting points for watershed segmentation of the gradient magnitude image. The fully automatic seeding is done in a generous fashion, so that at least one seed will be set in each foreground object. If more than one seed is placed in a single object, the watershed segmentation will lead to an initial over‐segmentation, i.e. a boundary is created where there is no strong edge. Thus, the result of the initial segmentation is further refined by merging based on the gradient magnitude along the boundary separating neighbouring objects. This step also makes it easy to remove objects with poor contrast. As a final step, clusters of nuclei are separated, based on the shape of the cluster. The number of input parameters to the full segmentation procedure is only five. These parameters can be set manually using a test image and thereafter be used on a large number of images created under similar imaging conditions. This automated system was verified by comparison with manual counts from the same image fields. About 90% correct segmentation was achieved for two‐ as well as three‐dimensional images.     

Towards the imaging of Weibel–Palade body biogenesis by serial block face‐scanning electron microscopy

Electron microscopy is used in biological research to study the ultrastructure at high resolution to obtain information on specific cellular processes. Serial block face‐scanning electron microscopy is a relatively novel electron microscopy imaging technique that allows three‐dimensional characterization of the ultrastructure in both tissues and cells by measuring volumes of thousands of cubic micrometres yet at nanometre‐scale resolution. In the scanning electron microscope, repeatedly an image is acquired followed by the removal of a thin layer resin embedded biological material by either a microtome or a focused ion beam. In this way, each recorded image contains novel structural information which can be used for three‐dimensional analysis. Here, we explore focused ion beam facilitated serial block face‐scanning electron microscopy to study the endothelial cell–specific storage organelles, the Weibel–Palade bodies, during their biogenesis at the Golgi apparatus. Weibel–Palade bodies predominantly contain the coagulation protein Von Willebrand factor which is secreted by the cell upon vascular damage. Using focused ion beam facilitated serial block face‐scanning electron microscopy we show that the technique has the sensitivity to clearly reveal subcellular details like mitochondrial cristae and small vesicles with a diameter of about 50 nm. Also, we reveal numerous associations between Weibel–Palade bodies and Golgi stacks which became conceivable in large‐scale three‐dimensional data. We demonstrate that serial block face‐scanning electron microscopy is a promising tool that offers an alternative for electron tomography to study subcellular organelle interactions in the context of a complete cell.     

Comparison of three‐dimensional analysis and stereological techniques for quantifying lithium‐ion battery electrode microstructures

Lithium‐ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium‐ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3‐D imaging techniques, quantitative assessment of 3‐D microstructures from 2‐D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two‐dimensional (2‐D) data sets. In this study, stereological prediction and three‐dimensional (3‐D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium‐ion battery electrodes were imaged using synchrotron‐based X‐ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2‐D image sections generated from tomographic imaging, whereas direct 3‐D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2‐D image sections is bound to be associated with ambiguity and that volume‐based 3‐D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially‐dependent parameters, such as tortuosity and pore‐phase connectivity.     

Automated three-dimensional analysis of particle measurements using an optical profilometer and image analysis software

The automated collection of topographic images from an optical profilometer coupled with existing image analysis software offers the unique ability to quantify three‐dimensional particle morphology. Optional software available with most optical profilers permits automated collection of adjacent topographic images of particles dispersed onto a suitable substrate. Particles are recognized in the image as a set of continuous pixels with grey‐level values above the grey level assigned to the substrate, whereas particle height or thickness is represented in the numerical differences between these grey levels. These images are loaded into remote image analysis software where macros automate image processing, and then distinguish particles for feature analysis, including standard two‐dimensional measurements (e.g. projected area, length, width, aspect ratios) and third‐dimensional measurements (e.g. maximum height, mean height). Feature measurements from each calibrated image are automatically added to cumulative databases and exported to a commercial spreadsheet or statistical program for further data processing and presentation. An example is given that demonstrates the superiority of quantitative three‐dimensional measurements by optical profilometry and image analysis in comparison with conventional two‐dimensional measurements for the characterization of pharmaceutical powders with plate‐like particles.