Hypertext atlas of fetal and neonatal pathology

Hypertext atlas of fetal and neonatal pathology is a free resource for pregraduate students of medicine, pathologists and other health professionals dealing with prenatal medicine. The atlas can be found at http://www.muni.cz/atlases. The access is restricted to registered users. Concise texts summarize the gross and microscopic pathology, etiology, and clinical signs of both common and rare fetal and neonatal conditions. The texts are illustrated with over 300 images that are accompanied by short comments. The atlas offers histological pictures of high quality. Virtual microscope interface is used to access the high-resolution histological images. Fetal ultrasound video clips are included. Case studies integrate clinical history, prenatal ultrasonographic examination, gross pathology and histological features. The atlas is available in English (and Czech) and equipped with an active index. The atlas is suitable both for medical students and pathologists as a teaching and reference tool. The atlas is going to be further expanded while keeping the high quality of the images.     

Bayesian estimation of probabilistic atlas for tissue segmentation

Automatic anatomical brain image segmentation is still a challenge. In particular, algorithms have to address the partial volume effect (PVE) as well as the variability of the gray level of internal brain structures which may appear closer to gray matter (GM) than white matter (WM). Atlas based segmentation is one solution as it brings prior information. For such tasks, probabilistic atlases are very useful as they take account of the PVE information. In this paper, we provide a detailed analysis of a generative statistical model based on dense deformable templates that represents several tissue types observed in medical images. The inputs are gray level data whereas our atlas is composed of both an estimation of the deformation metric and probability maps of each tissue (called class). This atlas is used to guide the tissue segmentation of new images. Experiments are shown on brain T1 MRI datasets. This method only requires approximate pre-registration, as the latter is done jointly with the segmentation. Note however that an approximate registration is a reasonable pre-requisite given the application.     

A framework for the automated analysis of subcellular patterns in human protein atlas images

The systematic study of subcellular location patterns is required to fully characterize the human proteome, as subcellular location provides critical context necessary for understanding a protein's function. The analysis of tens of thousands of expressed proteins for the many cell types and cellular conditions under which they may be found creates a need for automated subcellular pattern analysis. We therefore describe the application of automated methods, previously developed and validated by our laboratory on fluorescence micrographs of cultured cell lines, to analyze subcellular patterns in tissue images from the Human Protein Atlas. The Atlas currently contains images of over 3000 protein patterns in various human tissues obtained using immunohistochemistry. We chose a 16 protein subset from the Atlas that reflects the major classes of subcellular location. We then separated DNA and protein staining in the images, extracted various features from each image, and trained a support vector machine classifier to recognize the protein patterns. Our results show that our system can distinguish the patterns with 83% accuracy in 45 different tissues, and when only the most confident classifications are considered, this rises to 97%. These results are encouraging given that the tissues contain many different cell types organized in different manners, and that the Atlas images are of moderate resolution. The approach described is an important starting point for automatically assigning subcellular locations on a proteome-wide basis for collections of tissue images such as the Atlas.     

Nonrigid Registration Regularized by Shape Information: Application to Atlas Construction of Cardiac CT Images

Cardiac atlases play an important role in the computer-aided diagnosis of cardiovascular diseases, in particular they need to deal with large and highly variable image datasets. In this paper, we propose a new nonrigid registration algorithm incorporating shape information, to produce comprehensive atlases. For one thing, the multiscale gradient orientation features of images are combined to form the construction of multifeature mutual information. Additionally, the shape information of multiple-objects in images is incorporated into the cost function for registration. We demonstrate the merits of the new registration algorithm on the 3D data sets of 15 patients. The experimental results show that the new registration algorithm can outperform the conventional intensity-based registration method. The obtained atlas can represent the cardiac structures more accurately.     

3-Dimensional Diffusion Tensor Imaging (DTI) Atlas of the Rat Brain

Anatomical atlases play an important role in the analysis of neuroimaging data in rodent neuroimaging studies. Having a high resolution, detailed atlas not only can expand understanding of rodent brain anatomy, but also enables automatic segmentation of new images, thus greatly increasing the efficiency of future analysis when applied to new data. These atlases can be used to analyze new scans of individual cases using a variety of automated segmentation methods. This project seeks to develop a set of detailed 3D anatomical atlases of the brain at postnatal day 5 (P5), 14 (P14), and adults (P72) in Sprague-Dawley rats. Our methods consisted of first creating a template image based on fixed scans of control rats, then manually segmenting various individual brain regions on the template. Using itk-SNAP software, subcortical and cortical regions, including both white matter and gray matter structures, were manually segmented in the axial, sagittal, and coronal planes. The P5, P14, and P72 atlases had 39, 45, and 29 regions segmented, respectively. These atlases have been made available to the broader research community.     

Infant brain atlases from neonates to 1- and 2-year-olds

Background

Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size.

Methodology

To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies.

Conclusions

We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/.     

Determination of three-dimensional imaging properties of a light microscope system. Partial confocal behavior in epifluorescence microscopy.

We have determined the three-dimensional image-forming properties of an epifluorescence microscope for use in obtaining very high resolution three-dimensional images of biological structures by image processing methods. Three-dimensional microscopic data is collected as a series of two-dimensional images recorded at different focal planes. Each of these images contains not only in-focus information from the region around the focal plane, but also out-of-focus contributions from the remainder of the specimen. Once the imaging properties of the microscope system are characterized, powerful image processing methods can be utilized to remove the out-of-focus information and to correct for image distortions. Although theoretical calculations for the behavior of an aberration-free microscope system are available, the properties of real lenses under the conditions used for biological observation are often far from an ideal. For this reason, we have directly determined the image-forming properties of an epifluorescence microscope under conditions relevant to biological observations. Through-focus series of a point object (fluorescently-coated microspheres) were recorded on a charge-coupled device image detector. From these images, the three-dimensional point spread function and its Fourier transform, the optical transfer function, were derived. There were significant differences between the experimental results and the theoretical models which have important implications for image processing. The discrepancies can be explained by imperfections of the microscope system, nonideal observation conditions, and partial confocal effects found to occur with epifluorescence illumination. Understanding the optical behavior of the microscope system has indicated how to optimize specimen preparation, data collection, and processing protocols to obtain significantly improved images.     

Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs). This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases. DTI images are modeled as high dimensional fields, with each voxel exhibiting a vector valued feature comprising of mean diffusivity (MD), fractional anisotropy (FA), and fiber angle. For each structure, the probability distribution of each element in the feature vector is modeled as a mixture of Gaussians, the parameters of which are estimated from the labeled atlases. The structure-specific feature vector is then used to parcellate the test image. For each atlas, a likelihood is iteratively computed based on the structure-specific vector feature. The likelihoods from multiple atlases are then fused. The updating and fusing of the likelihoods is achieved based on the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation problems. We first demonstrate the performance of the algorithm by examining the parcellation accuracy of 18 structures from 25 subjects with a varying degree of structural abnormality. Dice values ranging 0.8–0.9 were obtained. In addition, strong correlation was found between the volume size of the automated and the manual parcellation. Then, we present scan-rescan reproducibility based on another dataset of 16 DTI images – an average of 3.73%, 1.91%, and 1.79% for volume, mean FA, and mean MD respectively. Finally, the range of anatomical variability in the normal population was quantified for each structure.     

Serendipia: Castilla-La Mancha telepathology network

Nowadays, there is no standard solution for acquiring, archiving and communication of pathology digital images. In addition, there does not exist any commercial Pathology Information System (LIS) that can manage the relationship between the reports generated by the pathologist and their corresponding images. Due to this situation, the Healthcare Service of Castilla-La Mancha decided to create a completely digital Pathology Department, the project is called SERENDIPIA. SERENDIPIA project provides all the necessary image acquiring devices needed to cover all kind of images that can be generated in a Pathology Department. In addition, in the SERENDIPIA project an Information System was developed that allows it, on the one hand, to cover the daily workflow of a Pathology Department (including the storage and the manage of the reports and its images), and, on the other hand, the Information System provides a WEB telepathology portal with collaborative tools like second opinion.     

High-resolution digital brain atlases: a Hubble telescope for the brain

We describe implementation of a method for digitizing at microscopic resolution brain tissue sections containing normal and experimental data and for making the content readily accessible online. Web-accessible brain atlases and virtual microscopes for online examination can be developed using existing computer and internet technologies. Resulting databases, made up of hierarchically organized, multiresolution images, enable rapid, seamless navigation through the vast image datasets generated by high-resolution scanning. Tools for visualization and annotation of virtual microscope slides enable remote and universal data sharing. Interactive visualization of a complete series of brain sections digitized at subneuronal levels of resolution offers fine grain and large-scale localization and quantification of many aspects of neural organization and structure. The method is straightforward and replicable; it can increase accessibility and facilitate sharing of neuroanatomical data. It provides an opportunity for capturing and preserving irreplaceable, archival neurohistological collections and making them available to all scientists in perpetuity, if resources could be obtained from hitherto uninterested agencies of scientific support.     

Spatially-Explicit Estimation of Geographical Representation in Large-Scale Species Distribution Datasets

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.     

Recent developments and present status of telepathology.

Telepathology which is the diagnostic work of a pathologist at a distance has been developed to routine application within the last ten years. It can be classified in relation to application, technical solutions, or performance conditions. Diagnostic pathology performance distinguishes primary diagnosis (for example, frozen section statement) from secondary diagnosis (for example, expert consultation) and quality assurance (diagnostic accuracy, continuous education and training). Applications comprise (a) frozen section service; (b) expert consultations; (c) remote control measurements; and (d) education and training. The technical solutions distinguish active (remote control, live imaging) systems from passive (conventional microscope handling, static imaging), and the performance systems with interactive (on-line, live imaging) use from those with passive (offline, static imaging) practice. Intra-operative frozen section service is mainly performed with remote control systems; whereas expert consultations and education/training are commonly based upon Internet connections with static imaging in an off-line mode. The image quality, transfer rates, and screen resolution of active and passive telepathology systems are sufficient for an additional or primary judgment of histological slides and cytological smears. From the technical point of view, remote control telepathology requires a fast transfer and at least near on-line judgement of images, i.e., image acquisition, transfer and presentation can be considered one performance function. Thus, image size, line transfer rate and screen resolution define the practicability of the system. In expert consultation, the pixel resolution of images and natural color presentation are the main factors for diagnostic support, whereas the line transfer rate is of minor importance. These conditions define the technical compartments, especially size and resolution of camera and screen. The performance of commercially available systems has reached a high quality standard. Pathologists can be trained in a short time and use the systems in a routine manner. Several telepathology systems have been implemented in large Institutes of Pathology which serve for frozen section diagnosis in small hospitals located in the local area. In contrast, expert consultation is mainly performed with international connections. There is a remarkable increase of expert consultations by telepathology according to the experiences of the Armed Forces Institute of Pathology or the Department of Pathology, Thoraxklinik, Heidelberg. In expansion of these experiences, a "globalization" of telepathology can be expected. Telepathology can be used to shrink the period necessary for final diagnosis by request for diagnostic assistance to colleagues working in appropriate related time zones. Telepathology is, therefore, not a substitute of conventional diagnostic procedures but a real improvement in the world of pathology.     

超高灵敏度荧光显微成像技术对光敏剂细胞内分布的初步研究

目的：探讨应用基于ICCD的超高灵敏度荧光显微成像系统研究光敏剂细胞内分布的可行性。方法：传代培养内皮细胞、食管癌细胞和肺癌细胞,将不同浓度血卟啉单甲醚(HMME)与细胞共同孵育不同时间。采用荧光显微镜及ICCD组成的荧光显微成像系统采集不同浓度及不同孵育时间条件下HMME的荧光图像,并采用计算机图像处理技术进行图像增强、滤波后计算其细胞浆与细胞核的平均荧光强度比值。同时应用激光共聚焦显微镜图像采集进行对比。结果：HMME浓度为5μg／ml时,荧光显微镜采集到HMME的荧光图像;HMME浓度升高到160μg／ml,激光共聚焦显微镜获得HMME的荧光图像。两组图像的特点都为胞浆中荧光强度较高,细胞核区荧光较弱;细胞浆与细胞核的比值约为2～3：1。结论：荧光显微镜和ICCD采集细胞内光敏剂的荧光图像灵敏度高,方法可靠、实用。HMME较多分布在细胞质中,细胞核吸收较少。     

Book Reviews

Books review in this article:
Practical Histochemistry. 2nd edn. Chayen & Bitensky
A Colour Atlas of Breast Pathology. M. Trojani     

Time resolved imaging microscopy. Phosphorescence and delayed fluorescence imaging.

An optical microscope capable of measuring time resolved luminescence (phosphorescence and delayed fluorescence) images has been developed. The technique employs two phase-locked mechanical choppers and a slow-scan scientific CCD camera attached to a normal fluorescence microscope. The sample is illuminated by a periodic train of light pulses and the image is recorded within a defined time interval after the end of each excitation period. The time resolution discriminates completely against light scattering, reflection, autofluorescence, and extraneous prompt fluorescence, which ordinarily decrease contrast in normal fluorescence microscopy measurements. Time resolved image microscopy produces a high contrast image and particular structures can be emphasized by displaying a new parameter, the ratio of the phosphorescence to fluorescence. Objects differing in luminescence decay rates are easily resolved. The lifetime of the long lived luminescence can be measured at each pixel of the microscope image by analyzing a series of images that differ by a variable time delay. The distribution of luminescence decay rates is displayed directly as an image. Several examples demonstrate the utility of the instrument and the complementarity it offers to conventional fluorescence microscopy.     

Modular Scanning Confocal Microscope with Digital Image Processing

In conventional confocal microscopy, a physical pinhole is placed at the image plane prior to the detector to limit the observation volume. In this work, we present a modular design of a scanning confocal microscope which uses a CCD camera to replace the physical pinhole for materials science applications. Experimental scans were performed on a microscope resolution target, a semiconductor chip carrier, and a piece of etched silicon wafer. The data collected by the CCD were processed to yield images of the specimen. By selecting effective pixels in the recorded CCD images, a virtual pinhole is created. By analyzing the image moments of the imaging data, a lateral resolution enhancement is achieved by using a 20 × / NA = 0.4 microscope objective at 532 nm laser wavelength.     

Focussed ion beam milling and scanning electron microscopy of brain tissue

This protocol describes how biological samples, like brain tissue, can be imaged in three dimensions using the focussed ion beam/scanning electron microscope (FIB/SEM). The samples are fixed with aldehydes, heavy metal stained using osmium tetroxide and uranyl acetate. They are then dehydrated with alcohol and infiltrated with resin, which is then hardened. Using a light microscope and ultramicrotome with glass knives, a small block containing the region interest close to the surface is made. The block is then placed inside the FIB/SEM, and the ion beam used to roughly mill a vertical face along one side of the block, close to this region. Using backscattered electrons to image the underlying structures, a smaller face is then milled with a finer ion beam and the surface scrutinised more closely to determine the exact area of the face to be imaged and milled. The parameters of the microscope are then set so that the face is repeatedly milled and imaged so that serial images are collected through a volume of the block. The image stack will typically contain isotropic voxels with dimenions as small a 4 nm in each direction. This image quality in any imaging plane enables the user to analyse cell ultrastructure at any viewing angle within the image stack.     

Raising the bar for the next generation of biological atlases: using existing data to inform the design and implementation of atlas monitoring

Selecting a sampling design to monitor multiple species across a broad geographical region can be a daunting task and often involves tradeoffs between limited resources and the accurate estimation of population abundance and occurrence. Since the 1950s, biological atlases have been implemented in various regions to document the occurrence of plant and animal species. As next‐generation atlases repeat original surveys, investigators often seek to raise the rigour of atlases by incorporating species abundances. We present a repeatable framework that incorporates existing monitoring data, hierarchical modelling and sampling simulations to augment existing atlas occurrence and breeding status maps with a secondary sampling of species abundances. Using existing information on three bird species with varying abundance and detectability, we evaluated several sampling scenarios for the 2nd Wisconsin Breeding Bird Atlas. In general, we found that most sampling schemes produced accurate mean statewide abundance estimates for species with medium to high abundance and detection probability, but estimates varied significantly for species with low abundance and low detection probability. Our approach provided a statewide point‐count sampling design that: provided precise and unbiased abundance estimates for species of varied prevalence and detectability; ensured suitable spatial coverage across the state and its habitats; and reduced spending on total survey costs. Our framework could benefit investigators conducting atlases and other broad‐scale avian surveys that seek to add systematic, multi‐species sampling for estimating density and abundance across broad geographical regions.     

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

IntroductionNeurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients.MethodsUsing publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients.ResultsThe parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes.DiscussionTo our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease.