Confocal DNA cytometry: a contour-based segmentation algorithm for automated three-dimensional image segmentation

BACKGROUND: Confocal laser scanning microscopy (CLSM) presents the opportunity to perform three-dimensional (3D) DNA content measurements on intact cells in thick histological sections. So far, these measurements have been performed manually, which is quite time-consuming. METHODS: In this study, an intuitive contour-based segmentation algorithm for automatic 3D CLSM image cytometry of nuclei in thick histological sections is presented. To evaluate the segmentation algorithm, we measured the DNA content and volume of human liver and breast cancer nuclei in 3D CLSM images. RESULTS: A high percentage of nuclei could be segmented fully automatically (e.g., human liver, 92%). Comparison with (time-consuming) interactive measurements on the same CLSM images showed that the results were well correlated (liver, r = 1.00; breast, r = 0.92). CONCLUSIONS: Automatic 3D CLSM image cytometry enables measurement of volume and DNA content of large numbers of nuclei in thick histological sections within an acceptable time. This makes large-scale studies feasible, whereby the advantages of CLSM can be exploited fully. The intuitive modular segmentation algorithm presented in this study detects and separates overlapping objects, also in two-dimensional (2D) space. Therefore, this algorithm may also be suitable for other applications.     

Number of nucleoli in various cell types of the mouse

The nucleoli of cells of the adult mouse were examined by staining with toluidine blue after removal of deoxyribonucleic acid from tissue sections by deoxyribonuclease treatment. The nuclei of each cell type examined contained one or more nucleoli. This was observed even in lymphocytes and neuroglia, although these cells have occasionally been described as anucleolated. In mature spermatids and spermatozoa, however, it was not possible to detect a nucleolus. The distribution of the number of nucleoli in many diploid cells exhibited a mode of two or three nucleoli per nucleus, and a range from 1 to 6 nucleoli. In presumedly diploid hepatic nuclei, the maximum number of nucleoli was six; but in presumedly tetraploid hepatic nuclei, it was 11. Thus, nearly twice as many nucleoli are present when the chromosome number is doubled. In view of this observation, it is suggested that six nucleolar organizers are present in the diploid chromosomal complement of the mouse. However, through failure of some nucleolar organizers or more probably through fusion of nucleoli, the number of these organelles in most nuclei is less than six.     

Electron microscopic and biochemical characteristics of nuclei and nucleoli isolated from rat liver

Rat liver nuclei were freed of cytoplasmic contamination by washing with Triton-X-100 and subsequent centrifugation through 2.2 M sucrose. Electron microscopic examination showed that the outer membranes of the nuclei had been removed, but that the nuclei otherwise resembled the nuclei of intact liver. Morphological studies, chemical estimations of DNA, RNA, and protein and the estimation of cytoplasmic "marker" enzymes suggested that contamination of nuclei by cytoplasmic components was limited. These nuclei were obtained in yields of about 70% and were suitable for the isolation of nucleoli. Nucleoli were isolated by the breaking of the nuclei by ultrasound and subsequent differential centrifugation. In ultrastructural appearance, the isolated nucleoli resembled nucleoli in intact tissue. However, at high magnifications the "granular" component of isolated nucleoli appeared to consist of tightly twisted fibers. The nucleoli could be obtained in yields of at least 30%, and the values for the chemical composition of the isolated nucleoli agreed with values previously reported.     

Histology and ultrastructure of the hepatopancreas of the tigerfish,Hydrocynus forskahlii

Study of the histology and ultrastructure of the hepatopancreas of the tigerfish, Hydrocynus forskahlii shows that the liver parenchyma is divided into irregularly shaped lobules, separated by the exocrine pancreas and associated connective tissue. The hepatocytes are arranged in interconnecting cords or laminae, two to three cell layers in thickness. Sinusoids separate the laminae. The spherical to oval-shaped hepatocytes contain large, round, centrally situated nuclei with prominent nucleoli. The cytoplasm of the hepatocytes contains abundant rough and smooth endoplasmic reticulae, free polysomes, and mitochondria. Exocrine pancreatic tissue is scattered throughout the liver. This tissue is encapsulated by an endothelium resting on a thin layer of connective tissue and is separated from the liver parenchyma by a sinusoid. The nuclei of the exocrine pancreas cells are spherical, basally situated within the cells, and contain dark nucleoli. Vesicular rough endoplasmic reticulae and secretory granules lie in the apical regions of the exocrine pancreas cells. © 1996 Wiley-Liss, Inc.     

The Problem of Nucleolar Number in Cell Nuclei and in Sections of Cell Nuclei

In this paper the mean number N of nucleoli of cell nuclei and the relative frequency PN of cell nuclei with N nucleoli are investigated. To solve the first problem, the stereological model of convex shaped nuclei and nucleoli and the assumption of randomly-isotropically distributed objects in space are used. The model is developed for non-vanishing thickness T of tissue sections. The relationship between the unknown number N of nucleoli in cell nuclei and the mean number n of nucleoli in nuclear sections determined by counting is N = n (D+T)/(d + T). Here D and d are the mean values of caliper diameter for nuclei and for nucleoli, resp. The second problem is illustrated by means of some biomedical examples: The relative frequency PN of cell nuclei with N nucleoli can be approximated by a generalized Poisson distribution in all investigated cases. Therefore the mean nucleolar number N is the essential parameter to describe the frequencies of cell nuclei with different numbers of nucleoli.     

Automated cell nuclear segmentation in color images of hematoxylin and eosin-stained breast biopsy

OBJECTIVE: To develop an automated, reproducible epithelial cell nuclear segmentation method to quantify cytologic features quickly and accurately from breast biopsy. STUDY DESIGN: The method, based on fuzzy c-mean clustering of the hue-band of color images and the watershed transform, was applied to 39 images from 3 histologic types (typical hyperplasia, atypical hyperplasia, and ductal carcinoma in situ [cribriform and solid]). RESULTS: The performance of the segmentation algorithm was evaluated by visually determining the percentage of badly segmented nuclei (approximately 25% for all types), the percentage of nuclei that remained in clumps (4.5-16.7%) and the percentage of missed nuclei (0.4-1.5%) for each image. CONCLUSION: The segmentation algorithm was sensitive in that a small percentage of nuclei were missed. However, the percentage of badly segmented nuclei was on the order of 25%, and the percentage of nuclei that remained in clumps was on the order of 10% of the total number of nuclei in the duct. Even so, > 600 nuclei per duct, on average, were segmented correctly; that was a sufficient number by which to calculate accurate quantitative, cytologic, morphometric measurements of epithelial cell nuclei in stained tissue sections of breast biopsy.     

Automated segmentation of routinely hematoxylin-eosin-stained microscopic images by combining support vector machine clustering and active contour models

OBJECTIVE: To develop a method for the automated segmentation of images of routinely hematoxylin-eosin (H-E)-stained microscopic sections to guarantee correct results in computer-assisted microscopy. STUDY DESIGN: Clinical material was composed 50 H-E-stained biopsies of astrocytomas and 50 H-E-stained biopsies of urinary bladder cancer. The basic idea was to use a support vector machine clustering (SVMC) algorithm to provide gross segmentation of regions holding nuclei and subsequently to refine nuclear boundary detection with active contours. The initialization coordinates of the active contour model were defined using a SVMC pixel-based classification algorithm that discriminated nuclear regions from the surrounding tissue. Starting from the boundaries of these regions, the snake fired and propagated until converging to nuclear boundaries. RESULTS: The method was validated for 2 different types of H-E-stained images. Results were evaluated by 2 histopathologists. On average, 94% of nuclei were correctly delineated. CONCLUSION: The proposed algorithm could be of value in computer-based systems for automated interpretation of microscopic images.     

In situ ultrastructural localization of sugar-binding sites in lizard granulosa cell nuclei

Mannose-binding sites were detected at the ultrastructural level in nuclei of lizard granulosa cells in situ by means of mannosylated ferritin. When ultrathin sections of material embedded in glycol methacrylate were incubated with mannosylated ferritin, a strong labelling was observed over nucleoli, chromatin and the external leaflet of the nuclear envelope, but no labelling was detected in the perinuclear space except for nuclear pores. This labelling was clearly inhibited when sections were incubated in a solution containing both mannosylated ferritin and a sugar-related neoglycoprotein (mannosylated serum albumin). These ultrastructural data supporting the existence of nuclear lectin-like components in reptilian cells are in agreement with our previous findings about such components in nuclei isolated from mammalian cells. Owing to the unique organization of the granular component of the nucleoli in specialized granulosa cells, we are able to show that some of the mannose-binding sites are associated with ribosomal precursors.     

Automatic image segmentation of nuclear stained breast tissue sections using color active contour model and an improved watershed method

Automatic image segmentation of immunohistologically stained breast tissue sections helps pathologists to discover the cancer disease earlier. The detection of the real number of cancer nuclei in the image is a very tedious and time consuming task. Segmentation of cancer nuclei, especially touching nuclei, presents many difficulties to separate them by traditional segmentation algorithms. This paper presents a new automatic scheme to perform both classification of breast stained nuclei and segmentation of touching nuclei in order to get the total number of cancer nuclei in each class. Firstly, a modified geometric active contour model is used for multiple contour detection of positive and negative nuclear staining in the microscopic image. Secondly, a touching nuclei method based on watershed algorithm and concave vertex graph is proposed to perform accurate quantification of the different stains. Finally, benign nuclei are identified by their morphological features and they are removed automatically from the segmented image for positive cancer nuclei assessment. The proposed classification and segmentation schemes are tested on two datasets of breast cancer cell images containing different level of malignancy. The experimental results show the superiority of the proposed methods when compared with other existing classification and segmentation methods. On the complete image database, the segmentation accuracy in term of cancer nuclei number is over than 97%, reaching an improvement of 3–4% over earlier methods.     

Automatic segmentation and supervised learning-based selection of nuclei in cancer tissue images

Analysis of preferential localization of certain genes within the cell nuclei is emerging as a new technique for the diagnosis of breast cancer. Quantitation requires accurate segmentation of 100-200 cell nuclei in each tissue section to draw a statistically significant result. Thus, for large-scale analysis, manual processing is too time consuming and subjective. Fortuitously, acquired images generally contain many more nuclei than are needed for analysis. Therefore, we developed an integrated workflow that selects, following automatic segmentation, a subpopulation of accurately delineated nuclei for positioning of fluorescence in situ hybridization-labeled genes of interest. Segmentation was performed by a multistage watershed-based algorithm and screening by an artificial neural network-based pattern recognition engine. The performance of the workflow was quantified in terms of the fraction of automatically selected nuclei that were visually confirmed as well segmented and by the boundary accuracy of the well-segmented nuclei relative to a 2D dynamic programming-based reference segmentation method. Application of the method was demonstrated for discriminating normal and cancerous breast tissue sections based on the differential positioning of the HES5 gene. Automatic results agreed with manual analysis in 11 out of 14 cancers, all four normal cases, and all five noncancerous breast disease cases, thus showing the accuracy and robustness of the proposed approach. ? Published 2012 Wiley Periodicals, Inc.     

Automatic segmentation of cell nuclei in Feulgen-stained histological sections of prostate cancer and quantitative evaluation of segmentation results

Digital image analysis of cell nuclei is useful to obtain quantitative information for the diagnosis and prognosis of cancer. However, the lack of a reliable automatic nuclear segmentation is a limiting factor for high-throughput nuclear image analysis. We have developed a method for automatic segmentation of nuclei in Feulgen-stained histological sections of prostate cancer. A local adaptive thresholding with an object perimeter gradient verification step detected the nuclei and was combined with an active contour model that featured an optimized initialization and worked within a restricted region to improve convergence of the segmentation of each nucleus. The method was tested on 30 randomly selected image frames from three cases, comparing the results from the automatic algorithm to a manual delineation of 924 nuclei. The automatic method segmented a few more nuclei compared to the manual method, and about 73% of the manually segmented nuclei were also segmented by the automatic method. For each nucleus segmented both manually and automatically, the accuracy (i.e., agreement with manual delineation) was estimated. The mean segmentation sensitivity/specificity were 95%/96%. The results from the automatic method were not significantly different from the ground truth provided by manual segmentation. This opens the possibility for large-scale nuclear analysis based on automatic segmentation of nuclei in Feulgen-stained histological sections.     

THE FINE STRUCTURE OF THE NUCLEOLUS IN MITOTIC DIVISIONS OF CHINESE HAMSTER CELLS IN VITRO

The nucleolus of Chinese hamster tissue culture cells (strain Dede) was studied in each stage of mitosis with the electron microscope. Mitotic cells were selectively removed from the cultures with 0.2 per cent trypsin and fixed in either osmium tetroxide or glutaraldehyde followed by osmium tetroxide. The cells were embedded in both prepolymerized methacrylate and Epon 812. Thin sections of interphase nucleoli revealed two consistent components; dense 150-A granules and fine fibrils which measured 50 A or less in diameter. During prophase, distinct zones which were observed in some interphase nucleoli (i.e. nucleolonema and pars amorpha) were lost and the nucleoli were observed to disperse into smaller masses. By late prophase or prometaphase, the nucleoli appeared as loosely wound, predominantly fibrous structures with widely dispersed granules. Such structures persisted throughout mitosis either free in the cytoplasm or associated with the chromosomes. At telophase, those nucleolar bodies associated with the chromosomes became included in the daughter nuclei, resumed their compact granular appearance, and reorganized into an interphase-type structure.     

Segmentation of cell nuclei in tissue section analysis

Image segmentation is a critical step in digital picture analysis, especially for that of tissue sections. As the morphology of the cell nuclei provides important biological information, their segmentation is of particular interest. The known segmentation methods are not adequate for segmenting cell nuclei of tissue sections; the reason for this lies in the optical properties of their images. We have developed new gradient methods of segmentation of previously presegmented images by taking these properties into account and by using the approximately circular shape of the cell nuclei as a priori information. In our first technique, the segment method, the images of the nuclei are divided into eight segments, special gradient filters being defined for each segment. This has enabled us to improve the gradient image. After searching for local maxima, the contours of nuclei can be found. In the second method, the method of transformation into the polar coordinate system (PCS), the a priori information serves to define a circular direction field for gradient computation and contour finding. In contrast with the first method, which offers a rapid, general idea about the nuclear shape, the PCS method permits precise segmentation and morphological analysis of the cell nuclei.     

Logistic regression analysis of low grade spindle cell lesions. A cytologic study

OBJECTIVE: To identify key diagnostic cytologic criteria for various low grade spindle cell lesions. STUDY DESIGN: We reviewed 20 synovial sarcomas, 18 benign neural tumors, 10 reparative lesions, 24 other benign and 27 additional malignant low grade spindle cell lesions. All specimens were coded as to the presence or absence of the following variables: high cellularity, tissue fragments, tissue culture appearance, epithelial fragments, vessel fragments, vascular arcades, fibrillar ground substance, myxoid background, microcystic areas, parallel arrangement of nuclei, naked nuclei, single cells, binucleate cells, multinucleate cells, long filamentous cells, short spindle cells, stellate cells, lipoblasts, nuclear pleomorphism, nuclei with pointed ends, comma/fishhook nuclei, cigar-shaped nuclei, ovoid/round nuclei, small nucleoli, large nucleoli, mitotic figures, intranuclear vacuoles and background histiocytes. A logistic regression analysis was performed to identify the variables predictive of malignant lesions, specifically synovial sarcomas, benign neural tumors and reparative lesions. RESULTS: Statistical analysis selected high cellularity, short spindle cells, small nucleoli and absence of tissue culture appearance as the main criteria for malignant neoplasms. Tissue fragments and high cellularity were selected as the primary criteria and absence of long filamentous cells and of myxoid background as the secondary criteria for synovial sarcomas. It selected fibrillar ground substance and absence of ovoid/round nuclei as the key criteria for benign neural tumors. The presence of a tissue culture appearance was the major criterion for reparative lesions. CONCLUSION: There are many previously described cytologic criteria, but we found that when subjected to statistical analysis, only a few features were significant in the evaluation of low grade spindle cell lesions.     

Changes in nurse cell nuclei during synchronous infection with Trichinella spiralis

The rate of enlargement of nuclei was determined on 4-microns-thick sections of synchronously infected mouse thigh muscle. Normal muscle nuclei had a geometric mean volume of 84 microns and a range of 42-170 microns 3. At days 5, 6, 7, 8, and 10 and 6 mo after infection, mean nuclear volume was 177 (100-315) microns 3, 254 (140-462) microns 3, 278 (172-447) microns 3, 681 (407-1,138) microns 3, 512 (326-804) microns 3, and 509 (298-870) microns 3, respectively. Size of nuclei for any given day followed a log normal distribution. On days 7 and 8 after infection, 31% of enlarged nuclei had 2 nucleoli, whereas only 15% had 2 nucleoli on day 10. One percent of enlarged nuclei in 6-mo-old nurse cells had double nucleoli. The number of enlarged nuclei in 6-mo-old nurse cells was determined from serial sections of infected tongue muscle. Each nurse cell contained an average of 40 enlarged nuclei. Sixty-four percent of nurse cells examined (n = 55) had between 30 and 60 enlarged nuclei. However, there was great variation in the range (7-142). These results are discussed in relation to the development of the nurse cell.     

An argyrophil III method for the demonstration of micro- and oligodendroglia

Micro- and oligodendroglia, plasma and nucleoli of nerve cells, capillary wall and nuclei of astrocytes become visible when sections of formol fixed human brain are immersed, without any previous treatment, into a physical developer of pH 10.5. The staining is inhibited by the catalytic activity of the tissue elements involved. By means of pretreatments with 1% performic acid and 30% sodium rhodanide dissolved in 0.4% sodium hydroxide, the catalytic activity in the unwanted tissue elements is suppressed, and this results in an elective demonstration of micro- and oligodendroglia. Reducing groups of the tissue or any kind of performed nuclei play no role in this silver staining.     

Morphological and Histochemical Changes Occurring during the Life-span of Root-tip Galls on Lolium perenne Induced by Longidorus elongatus

The RNA and protein content of perennial ryegrass root-tip galls induced by Longidorus elongatus were measured from transverse sections and the morphology described. Galls progressed through five distinct stages and were viable for only 10-12 days at 18 C, after which they collapsed and became necrotic. In the initial stage hypertrophy occurred and cells contained enlarged nuclei and nucleoli, a greater proportion of cytoplasm, and increased concentrations of protein. This was followed by hyperplasia; cells divided to give two or four daughter cells, accompanied by a proportionate reduction in volumes of cytoplasm, nuclei, and nucleoli and reduced concentrations of RNA and protein. The third stage was secondary hypertrophy with enlarged, amoeboid nuclei and nucleoli and a significant increase in concentration of RNA and protein. In the final two stages, as feeding by L. elongatus progressively removed cell contents, most cells were devoid of inclusions and galls collapsed and were invaded by soil bacteria. This ordered development and exploitation of galls suggests that L. elongatus may have two phases in its feeding.     

A Pulse Coupled Neural Network Segmentation Algorithm for Reflectance Confocal Images of Epithelial Tissue

Automatic segmentation of nuclei in reflectance confocal microscopy images is critical for visualization and rapid quantification of nuclear-to-cytoplasmic ratio, a useful indicator of epithelial precancer. Reflectance confocal microscopy can provide three-dimensional imaging of epithelial tissue in vivo with sub-cellular resolution. Changes in nuclear density or nuclear-to-cytoplasmic ratio as a function of depth obtained from confocal images can be used to determine the presence or stage of epithelial cancers. However, low nuclear to background contrast, low resolution at greater imaging depths, and significant variation in reflectance signal of nuclei complicate segmentation required for quantification of nuclear-to-cytoplasmic ratio. Here, we present an automated segmentation method to segment nuclei in reflectance confocal images using a pulse coupled neural network algorithm, specifically a spiking cortical model, and an artificial neural network classifier. The segmentation algorithm was applied to an image model of nuclei with varying nuclear to background contrast. Greater than 90% of simulated nuclei were detected for contrast of 2.0 or greater. Confocal images of porcine and human oral mucosa were used to evaluate application to epithelial tissue. Segmentation accuracy was assessed using manual segmentation of nuclei as the gold standard.     

Immunocytochemical determination of ploidy class-dependent bromodeoxyuridine incorporation in rat liver parenchymal cells after partial hepatectomy

Summary Immunocytochemistry of bromodeoxyuridine (BrdU) incorporated in DNA was performed on cryostat sections of rat liver and on isolated hepatocytes after partial hepatectomy using a two-step labeling technique. The method enabled the detection of S-phase nuclei in both tissue preparations. Quantification of the number of labeled nuclei in sections showed that the number of nuclei in S-phase increased from 0.3% in control liver to about 36% at 24 h after partial hepatectomy. The detection of BrdU in isolated hepatocytes showed the same labeling index of binuclear diploid, mononuclear tetraploid and binuclear tetraploid cells. A special role for mononuclear diploid cells in proliferation did not seem to occur.