Image analysis of Nissl-stained neuronal perikarya in the primary visual cortex of the rat: automatic detection and segmentation of neuronal profiles with nuclei and nucleoli

The anatomical and functional specialization of the fusiform gyrus

The fusiform gyrus (FG) is commonly included in anatomical atlases and is considered a key structure for functionally-specialized computations of high-level vision such as face perception, object recognition, and reading. However, it is not widely known that the FG has a contentious history. In this review, we first provide a historical analysis of the discovery of the FG and why certain features, such as the mid-fusiform sulcus, were discovered and then forgotten. We then discuss how observer-independent methods for identifying cytoarchitectonical boundaries of the cortex revolutionized our understanding of cytoarchitecture and the correspondence between those boundaries and cortical folding patterns of the FG. We further explain that the co-occurrence between cortical folding patterns and cytoarchitectonical boundaries are more common than classically thought and also, are functionally meaningful especially on the FG and probably in high-level visual cortex more generally. We conclude by proposing a series of alternatives for how the anatomical organization of the FG can accommodate seemingly different theoretical aspects of functional processing, such as domain specificity and perceptual expertise.

Open source bioimage informatics for cell biology

Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery.

A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks

BACKGROUND

Automated segmentation of fluorescently-labeled cell nuclei in 3D confocal microscope images is essential to many studies involving morphological and functional analysis. A common source of segmentation error is tight clustering of nuclei. There is a compelling need to minimize these errors for constructing highly automated scoring systems.

METHODS

A combination of two approaches is presented. First, an improved distance transform combining intensity gradients and geometric distance is used for the watershed step. Second, an explicit mathematical model for the anatomic characteristics of cell nuclei such as size and shape measures is incorporated. This model is constructed automatically from the data. Deliberate initial over-segmentation of the image data is performed, followed by statistical model-based merging. A confidence score is computed for each detected nucleus, measuring how well the nucleus fits the model. This is used in combination with the intensity gradient to control the merge decisions.

RESULTS

Experimental validation on a set of rodent brain cell images showed 97% concordance with the human observer and significant improvement over prior methods.

CONCLUSIONS

Combining a gradient-weighted distance transform with a richer morphometric model significantly improves the accuracy of automated segmentation and FISH analysis.

Applying watershed algorithms to the segmentation of clustered nuclei

Cluster division is a critical issue in fluorescence microscopy-based analytical cytology when preparation protocols do not provide appropriate separation of objects. Overlooking clustered nuclei and analyzing only isolated nuclei may dramatically increase analysis time or affect the statistical validation of the results. Automatic segmentation of clustered nuclei requires the implementation of specific image segmentation tools. Most algorithms are inspired by one of the two following strategies: 1) cluster division by the detection of internuclei gradients; or 2) division by definition of domains of influence (geometrical approach). Both strategies lead to completely different implementations, and usually algorithms based on a single view strategy fail to correctly segment most clustered nuclei, or perform well just for a specific type of sample. An algorithm based on morphological watersheds has been implemented and tested on the segmentation of microscopic nuclei clusters. This algorithm provides a tool that can be used for the implementation of both gradient- and domain-based algorithms, and, more importantly, for the implementation of mixed (gradient- and shape-based) algorithms. Using this algorithm, almost 90% of the test clusters were correctly segmented in peripheral blood and bone marrow preparations. The algorithm was valid for both types of samples, using the appropriate markers and transformations.

Systematic investigations of the contrast results of histochemical stainings of neurons and glial cells in the human brain by means of image analysis

The investigation of neurohistological specimens by image analysis has become an important tool in morphological neuroscience. The problems which arise during the processing of these images are non-trivial, especially if a pattern recognition of cells in the imaged tissue is intended. One of the major problems faced concerns the segmentation of structures of interest, whether cells or other histologic structures. The segmentation problem is often the result of an inappropriate staining procedure. For serious image analysis to be performed, the material under investigation must be optimally prepared. Spatially complex patterns, e.g. fuzzy-like neighbouring neurons, are easy to recognize for humans. But the integrative and associative performance of current artificial neuronal network schemes is too low to achieve the same recognition quality as humans do. Therefore, a general analysis of staining characteristics was performed, especially with respect to those stains which are relevant to object segmentation. Although most image analytical investigations of tissues are based on stained samples, a study of this type has not been previously conducted. Of the stains and procedures evaluated, the gallocyanin chrome alum combination staining provided the best stain contrast. Furthermore, this staining method shows sufficient constancy within different parts of the human brain. Even the fine nuclear textures are differentiable and can be used for further pattern recognition procedures.

Advances in automated 3-D image analyses of cell populations imaged by confocal microscopy

Automated three-dimensional (3-D) image analysis methods are presented for rapid and effective analysis of populations of fluorescently labeled cells or nuclei in thick tissue sections that have been imaged three dimensionally using a confocal microscope. The methods presented here greatly improve upon our earlier work (Roysam et al.:J Microsc 173: 115-126, 1994). The principal advances reported are: algorithms for efficient data pre-processing and adaptive segmentation, effective handling of image anisotrophy, and fast 3-D morphological algorithms for separating overlapping or connected clusters utilizing image gradient information whenever available. A particular feature of this method is its ability to separate densely packed and connected clusters of cell nuclei. Some of the challenges overcome in this work include the efficient and effective handling of imaging noise, anisotrophy, and large variations in image parameters such as intensity, object size, and shape. The method is able to handle significant inter-cell, intra-cell, inter-image, and intra-image variations. Studies indicate that this method is rapid, robust, and adaptable. Examples were presented to illustrate the applicability of this approach to analyzing images of nuclei from densely packed regions in thick sections of rat liver, and brain that were labeled with a fluorescent Schiff reagent.

Automatic detection of clustered, fluorescent-stained nuclei by digital image-based cytometry

Automatic image-based cytometry (IC) can conveniently quantify the distributions of several specific, fluorescence-labeled molecules within individual, isolated cells of slide- or tissue-based specimens. However, many specimens contain clusters of cells or nuclei that are not detected as individual entities by existing automatic methods. We have developed analysis algorithms which detected individual nuclei occurring in clusters or as isolated nuclei. Specimens were labeled with a fluorescent DNA stain, imaged and the images were segmented into regions of nuclei and background. Clusters of nuclei, identified by their size and shape, were divided into individual nuclei by searching for dividing paths between nuclei. The paths, which need not be straight, possessed the highest average gradient per pixel. In addition, both high- and low-pass filtered images of the original image were analyzed. For each individual nucleus, one of the three segmented regions representing the nucleus (from either the original or one of two filtered images) was chosen as the final result, based on the closeness of the regions to average nuclear morphology. The algorithms correctly detected a high proportion of isolated (328/333) and clustered (254/271) nuclei when applied to images of 2 microns prostate and breast cancer sections. Thus, these algorithms should enable much more accurate detection and analyses of nuclei in intact specimens.

Automated image analyzing system for the quantitative study of living cells in culture

A fully automated image analyzing system was developed for the quantitative study of cells in culture. It was able to count cells, to classify cells according to their morphological characteristics and to follow cell culture development. A specific procedure was designed to process Hoffman modulation contrast images. It detects local gray level differences while using conditional dilation techniques. We were able to successfully detect aggregated unstained cells, presently a technical limit in image segmentation. Living cells can be studied in a noninvasive and nondestructive way with this system. An improved automatic focusing algorithm was developed which ensured an accurate prediction of the optimal focus position. A strictly defined sampling procedure was applied to estimate unbiasedly cell density and obtain precisely cell contours. The evaluation of the system was carried out on Chinese hamster ovary (CHO-NTR) cell cultures treated with a newly developed neurotensin agonist JMV449. Chinese hamster ovary cell division was found to be retarded 20 hours after the JMV449 treatment, while the morphology of CHO-NTR cells has already undergone significant changes 12 hours after the treatment. This image analyzing system provides the possibility to follow cell culture development (e.g., cell density evolution, cell morphological changes) under various experimental conditions.

Inhibition of angiogenesis in vitro and in ovo with an inhibitor of cellular protein kinases, MDL 27032

Protein kinase C (PKC) was implicated as an important positive regulator of angio-genesis by studies showing that tumor promoting phorbol esters, which activate PKC, stimulate angiogenesis both in vitro and in vivo. Therefore, inhibitors of PKC might be expected to block angiogenesis. MDL 27032 [4-propyl-5-(4-pyridinyl)-2(3H)-oxazolone], an inhibitor of cellular protein kinases, prevented capillary-like tube formation by human umbilical vein endothelial cells (HUVEC) on basement membrane preparations, an in vitro model for angiogenic activity. MDL 27032 had an IC50 = 50 microM, whereas MDL 27044, the 4-methyl analog of MDL 27032, was less effective (IC50 greater than 100 microM). This selectivity was reflected in the relative abilities of the two compounds to inhibit PKC and protein kinase A (PKA) activity prepared from HUVEC, and also to inhibit the basic fibroblast growth factor stimulated proliferation of HUVEC. MDL 27032 (0.3 microgram/egg) also significantly inhibited neovascularization in yolk sac membranes of developing chick embryos, whereas MDL 27044 added at concentrations up to 3 micrograms/egg was not inhibitory when compared with vehicle treated controls. Adhesion of HUVEC to individual extracellular matrix proteins, including laminin, fibronectin, and fibrinogen, but not to the mixture of matrix components or collagen type I and IV, was inhibited after treatment with MDL 27032. These studies suggest that MDL 27032, may have potential as an anti-angiogenic agent because it disrupts both formation of tube-like structures by HUVEC on Matrigel and normal neovascularization in ovo. This inhibition may in part be due to altered cellular interactions with the extracellular matrix.

Alzheimer's disease and aging: effects on perforant pathway perikarya and synapses

The hippocampal perforant pathway originates in the entorhinal cortex (ERC) and terminates in the outer molecular layer of the dentate gyrus (DG). To compare the effects of normal aging and Alzheimer's disease (AD) on the elements of the perforant pathway, we compared relative perikaryal numbers (determined by counting cell bodies and estimating volumes) in layer II of the ERC with synaptic quantities (estimated from immunoreactivity for the synaptic terminal protein synapsin I and DG volume) in the molecular layer of the DG. The brains of 5 young and 9 elderly cognitively normal individuals, and of 9 AD patients were studied. In normal aging we found a significant age-related decline in perikaryal numbers in the ERC without demonstrable synaptic loss in the DG. In AD there was marked and equivalent, (or proportional) reduction in both ERC perikaryal numbers and DG synapses. These data suggest that in normal aging remaining neurons may continue to support a full array of synapses, perhaps due to mechanisms such as axonal sprouting, synaptic enlargement, or synaptic ingrowth. In AD, however, the accelerated neuronal loss may overwhelm such compensatory mechanisms or alternatively, independent synaptic and perikaryal losses may occur.

Stereology: a method for analyzing images

This review deals with notions of shape, sizes, numbers, densities and orientation in space, all basic concepts in stereology. With the initiation by Delesse in 1847, but mainly since the beginning of the XXth century, many stereological methods have been published allowing us to relate two-dimensional measurements easily obtainable on flat histological images with three-dimensional characteristics of the structure analysed. Looking at these methods, the neurobiologist, generally impermeable to concepts of sampling, statistical bias, efficiency, cost of effort and distribution-free, is discountenanced and continues old laboratory usages and customs. Furthermore, for the last ten years, the advent of a plethora of new powerful tools, considered as assumption-free and more efficient than the previous ones, increase the risk proportionately the disarray of the potential user. The purpose of this review is to present synthetically all traditional and actual aspects of stereology in order to guide the reader in the labyrinth of this speciality. The necessarily short exposition is compensated by many references to which the beginner or the initiated can refer.