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Quantitation of noradrenaline nerve density in mouse iris by computer-assisted image analysis.

The density of noradrenaline (NA)-containing nerve fibres in mouse iris was measured with computer-assisted image analysis techniques both under normal conditions and during regeneration. Noradrenaline nerves were visualized by Falck-Hillarp formaldehyde condensation technique in whole-mount spread preparations of mouse irides. The samples were analysed in a fluorescence microscope connected to a commercially available image analysis system (IBAS/Kontron). A software program was developed for specific detection of fluorescence and the nerve density was determined by calculating the area covered by fluorescence in percentage of total measuring field. The method showed good reproducibility as observed both when repeated measurements were performed in the same measuring field or when consecutive measurements on the same set of irides were performed. Also the inter-assay variation between control values in the different experiments was low. Loading of the adrenergic nerves by incubation in alpha-methyl-NA or conditions leading to partial diffusion of the fluorophore had minor effects on the nerve density values. The regeneration of the NA nerve fibres after a selective toxic sympathectomy with 6-hydroxydopamine was also studied. The nerve fibre density values measured by image analysis correlated well with the uptake of [3H]NA; the endogenous NA levels recovered much more slowly, however. It thus seems that endogenous transmitter levels might be a somewhat insensitive index of nerve terminal regrowth, at least in early stages of regeneration. The results indicate that image analysis is a powerful tool to quantitate a transmitter-identified nerve terminal network in a histological preparation.

Adrenergic Fibers↗

Automated tri-image analysis of stored corneal endothelium.

BACKGROUND: Endothelial examination of organ culture stored corneas is usually done manually and on several mosaic zones. Some banks use an image analyser that takes account of only one zone. This method is restricted by image quality, and may be inaccurate if endothelial cell density (ECD) within the mosaic is not homogeneous. The authors have developed an analyser that has tools for automatic error detection and correction, and can measure ECD and perform morphometry on multiple zones of three images of the endothelial mosaic. METHODS: 60 human corneas were divided into two equal groups: group 1 with homogeneous mosaics, group 2 with heterogeneous ones. Three standard microscopy video images of the endothelium, graded by quality, were analysed either in isolation (so called mono-image analysis) or simultaneously (so called tri-image analysis), with 50 or 300 endothelial cells (ECs) counted. The automated analysis was compared with the manual analysis, which concerned 10 non-adjacent zones and about 300 cells. For each analysis method, failures and durations were studied according to image quality. RESULTS: All corneas were able to undergo analysis, in about 2 or 7.5 minutes for 50 and 300 ECs respectively. The tri-image analysis did not increase analysis time and never failed, even with mediocre images. The tri-image analysis of 300 ECs was always most highly correlated with the manual count, particularly in the heterogeneous cornea group (r=0.94, p<0.001) and prevented serious count errors. CONCLUSIONS: This analyser allows reliable and rapid analysis of ECD, even for heterogeneous endothelia mosaics and mediocre images.

Aged↗

Application of image analysis techniques in activated sludge wastewater treatment processes.

Image analytical techniques have been extensively developed to evaluate complex microbial aggregates such as sludge flocs and biofilms. This review covers the latest contributions concerning the application of image analysis to the activated sludge systems with respect to the most frequently used morphological parameters and relations between them and traditional wastewater treatment parameters. Recent developments have indicated that image analysis can be successfully used for the quantification of flocs and filamentous bacteria in the operating wastewater treatment plants, which enables prediction of bulking events and pinpoint flocs formation.

Bacteria↗

DNA ploidy status in 84 ocular melanomas: a study of DNA quantitation in ocular melanomas by flow cytometry and automatic and interactive static image analysis.

Deoxyribonucleic acid (DNA) ploidy was quantified in 84 ocular melanomas (median follow-up, 11-years) by flow cytometry, CAS 200 interactive image analysis, and Pathology Image Processing Environment (PIPE; Department of Quantitative Pathology, Free University, Amsterdam, The Netherlands) automatic image analysis (75). Overall, 32.1% of the melanomas were aneuploid, 2.3% were tetraploid, and 66.6% were diploid. Pathology Image Processing Environment analysis estimated DNA ploidy in 12 tumors that were unprocessable by flow cytometry. Of 10 tumors that were diploid by flow cytometry, PIPE detected stemline aneuploidy in five and some aneuploid cells in five more. Seven tumors were aneuploid by PIPE but diploid by CAS 200, five of which contained occasional DNA aneuploid cells on the CAS 200 histograms. Pathology Image Processing Environment analysis quantified tumor samples with an average of 500 (250 to 1,050) cells in less than 10 minutes. All cells classified as spindle A according to the Callender system (more than 10,000) were diploid. Spindle B and epithelioid cells occupied both diploid and aneuploid peaks on the DNA histograms. Dioxyribonucleic acid variables did not correlate with established prognosticators, such as Callender cell type, largest tumor dimension, or glaucoma, nor did they reach significance by univariate and multivariate analyses. The value of these findings as a diagnostic support in uveal melanoma, particularly in combination with fine needle aspiration biopsy, is discussed.

DNA, Neoplasm↗

Medical applications of image analysis with the Magiscan 2.

The previous generation of image analysis machines were capable of processing and analyzing binary, i.e., black and white images, and making measurements and decisions thereon. The Magiscan 2, one of the new generation computers, is capable of analyzing gray-level images in a variety of sophisticated ways. Its uses in the medical application of image analysis are presented, as are the techniques used to analyze images in general. The two principal current medical uses are the automatic karyotyping of chromosomes and the automatic screening of cervical smears. Other applications discussed include three-dimensional reconstruction of structures from two-dimensional sections and the possibility of developing expert systems for medical diagnostics.

Computers↗

Optimization of automatic portal image analysis.

The purpose of this study is to quantify and optimize the performance of an automatic portal image analysis procedure under clinical conditions and to compare the performance with that of human operators. A new method, based on analysis of variance, is introduced to quantify the clinical performance of portal image analysis tools in terms of systematic and random variations. The automatic portal image analysis procedure is based on chamfer matching. Two image enhancement techniques have been investigated in the automatic procedure: morphological top-hat (MTH) transformation and multiscale medial axis (MMA) transformation. The performance of these enhancements was quantified and optimized as a function of filter size using images obtained from clinical treatment. All images used for this study were obtained from pelvic treatment fields by means of an electronic portal imaging device. The random variations in the alignment of AP fields are typically 0.5 mm and 0.5 degrees (1 SD) for both the human operators and the optimized automatic analysis procedure. Random variations in the alignment of lateral pelvic fields are typically twice as large for all operators. MMA enhancement yields smaller random variations than MTH enhancement for lateral fields, but the differences are marginal for AP fields. The optimized automatic analysis procedure has a success rate ranging from 99% for AP large fields to 96% for lateral fields and 85% for AP boost fields. The accuracy of the method is comparable with the accuracy of the human operators for most investigated fields. For lateral boost fields and simultaneous boost fields, the random variations of the automatic analysis are typically two times larger than the variations of the human operators. Automatic analysis is 4 to 20 times faster than human operators yielding a large reduction in work load.

Analysis of Variance↗

Quantitative computerized image analysis of immunostained lymphocytes. A methodological approach.

A methodological approach by computerized image analysis to quantify immunostained objects in histological sections is described. We have investigated antibodies against CD4, CD8, CD20, CD23 and CD25 in frozen sections of human nasal mucosa; however, the methodology of standardization is of general validity. The study was designed particularly to investigate the following points: 1) light intensity, 2) the grey level for counter staining intensity, 3) the grey level threshold value for positive objects, 4) the minimal acceptable size of a positive object, 5) the influence of the brightness of the light on both the number and the area of objects. Furthermore, random sampling and determination of 6) the area per section, and 7) the number of histological sections to be measured per biopsy. Finally, a study of reproducibility of immunostaining intensity was performed. The influence of the different parameters mentioned above was studied and the values (eg. threshold value) for our particular setting of microscope, image analysis equipment, computer software etc, were defined. The method was then tested for intra- and interindividual variation which was found to be less than 5%. Correlation analysis of the reproducibility gave coefficients of correlation of 0.99, both concerning number of immunopositive objects and immunopositive area. We emphasize the importance of a highly standardized methodology if the numeric data obtained from computer assisted image analysis are to be more accurate than semiquantitative assessments by experienced observers. With a thorough standardization as described in this method it is possible to obtain numeric values, and data with low deviations, which are two obvious and important advantages.

Antigens, CD↗

Immunohistochemical determination of nuclear antigens by colour image analysis: application for labelling index, estrogen and progesterone receptor status in breast cancer.

The immunohistochemical evaluation of 5-bromo-2'-deoxyuridine (BrdU) labelling index, estrogen (ER) and progesterone receptor (PR) status was carried out on the automated computer-assisted image analysis station BIOCOM 500. Special software has been developed to measure nuclear antigens using the immunoperoxidase method with the Harris hematoxylin counterstain. The analysis was based on the different light adsorption spectra of the chromogen diaminobenzidine and Harris's hematoxylin coloration when exposed to light of differing wavelengths. The results obtained by image analysis were compared to previously validated methods. The thymidine labelling index performed by manual procedures and BrdU incorporation performed by image analysis were comparable (linear correlation coefficient r = 0.76, P < 0.001). Comparison of image analysis and dextran coated charcoal assay for ER and PR content revealed excellent sensitivities and specificities (linear correlation coefficient r = 0.87, P < 0.001 for ER and r = 0.93, P < 0.001 for PR). These data suggest that automated image analysis offers a reliable and reproducible procedure for measuring nuclear antigens.

Antigens, Neoplasm↗

Semi-automated measurement of motility of human subgingival microflora by image analysis.

The purpose of this investigation was to quantitatively estimate bacterial motility by image analysis, and to apply this method for the measurement of motility of human subgingival microflora. We developed a semi-automated method for the quantification of bacterial motility using video microscopy, digitization and image processing. Moving images of both authentic bacterial samples and clinical samples were recorded using a phase contrast microscope with a high speed (1/100 s) shutter camera. The motility was evaluated by measuring the total number of pixels remaining after the subtraction of 2 serial video images. The total number of pixels was significantly correlated with both the sum of the velocity of each bacterial cell and the number of motile bacteria on the same original images. Motility of subgingival microflora from 140 clinical samples tested was measured at 0 pixels to 3600 pixels, whereas the effect of Brownian movement was less than 150 pixels. The motility of subgingival microflora estimated with this image analysis system did not differ much from objective judgments by the naked eyes of experts. These results suggest that a semi-automated image analysis system may be useful in the evaluation of the motility of human subgingival microflora.

Adolescent↗

Object-based image analysis using multiscale connectivity.

This paper introduces a novel approach for image analysis based on the notion of multiscale connectivity. We use the proposed approach to design several novel tools for object-based image representation and analysis which exploit the connectivity structure of images in a multiscale fashion. More specifically, we propose a nonlinear pyramidal image representation scheme, which decomposes an image at different scales by means of multiscale grain filters. These filters gradually remove connected components from an image that fail to satisfy a given criterion. We also use the concept of multiscale connectivity to design a hierarchical data partitioning tool. We employ this tool to construct another image representation scheme, based on the concept of component trees, which organizes partitions of an image in a hierarchical multiscale fashion. In addition, we propose a geometrically-oriented hierarchical clustering algorithm which generalizes the classical single-linkage algorithm. Finally, we propose two object-based multiscale image summaries, reminiscent of the well-known (morphological) pattern spectrum, which can be useful in image analysis and image understanding applications.

Algorithms↗

HBM functional imaging analysis contest data analysis in wavelet space.

An analysis of the Functional Imaging Analysis Contest (FIAC) data is presented using spatial wavelet processing. This technique allows the image to be filtered adaptively according to the data itself, rather than relying on a predetermined filter. This adaptive filtering leads to better estimation of the parameters and contrasts in terms of mean squared error. It will be shown that by introducing a slight bias into the estimation, a large reduction in the variance can be achieved, leading to better overall mean squared error estimates. As no single filter needs to be preselected, results containing many scales of information can be found. In the FIAC data, it is shown that both small-scale and large-scale (smoother, more dispersed) effects occur. The combination of small- and large-scale effects detected in the FIAC data would be easy to miss using conventional single filter analysis.

Algorithms↗

Direct identification of pure Penicillium species using image analysis.

This paper presents a method for direct identification of fungal species solely by means of digital image analysis of colonies as seen after growth on a standard medium. The method described is completely automated and hence objective once digital images of the reference fungi have been established. Using a digital image it is possible to extract precise information from the surface of the fungal colony. This includes color distribution, colony dimensions and texture measurements. For fungal identification, this is normally done by visual observation that often results in a very subjective data recording. Isolates of nine different species of the genus Penicillium have been selected for the purpose. After incubation for 7 days, the fungal colonies are digitized using a very accurate digital camera. Prior to the image analysis each image is corrected for self-illumination, thereby gaining a set of directly corresponding images with respect to illumination. A Windows application has been developed to locate the position and size of up to three colonies in the digitized image. Using the estimated positions and sizes of the colonies, a number of relevant features can be extracted for further analysis. The method used to determine the position of the colonies will be covered as well as the feature selection. The texture measurements of colonies of the nine species were analyzed and a clustering of the data into the correct species was confirmed. This indicates that it is indeed possible to identify a given colony merely by macromorphological features. A classifier (in the normal distribution) based on measurements of 151 colonies incubated on yeast extract sucrose agar (YES) was used to discriminate between the species. This resulted in a correct classification rate of 100% when used on the training set and 96% using cross-validation. The same methods applied to 194 colonies incubated on Czapek yeast extract agar (CYA) resulted in a correct classification rate of 98% on the training set and 71% using cross-validation.

Color↗

Preliminary studies on scoring micronuclei by computerised image analysis.

Initial studies of the use of computerised image analysis to determine micronucleus frequencies in human lymphocytes that have completed one nuclear division are described. Two methods, based on (a) bromodeoxyuridine incorporation and (b) cytokinesis blocking with cytochalasin-B, were studied. The former method is directly amenable to automation. Cytokinesis-blocked cells could not be automatically recognised by image analysis but it was possible to obtain the correct micronucleus frequency from the integrated optical density histograms by using the mononucleate/binucleate cell ratio obtained by visual analysis. The mean (+/- 1 S.E.) integrated optical density of X-ray-induced micronuclei was 11.2% (+/- 1.1) of that measured for nuclei of G1 cells.

Automation↗

Reproducibility of quantitative measurement of white enamel demineralisation by image analysis.

The reproducibility of measuring artificial enamel white spot lesions from captured photographic images using computerised image analysis was assessed. Enamel lesions were induced on the buccal surface of 22 human teeth over periods of 3, 7 and 14 days. Standardised photographs were taken from above and below the occlusal plane. These were repeated after 2 weeks. The photographs were converted into TIFF images and mean grey scale levels of the areas of etched enamel were measured using computerised image analysis. Assessment of repeat readings of the same slide showed good reproducibility for photographs taken below the occlusal plane. The limits of agreement showed reasonable agreement between readings carried out on two slides of the same tooth. Capturing TIFF images via 35-mm film and measuring grey scale levels by computerised image analysis is a useful method of quantitative study of early enamel demineralisation. This may be developed for application in the clinical setting.

Adult↗

Comparison of corneal endothelial image analysis by Konan SP8000 noncontact and Bio-Optics Bambi systems.

PURPOSE: Compare corneal endothelial image analysis by Konan SP8000 and Bio-Optics Bambi image-analysis systems. METHODS: Corneal endothelial images from 98 individuals (191 eyes), ranging in age from 4 to 87 years, with a normal slit-lamp examination and no history of ocular trauma, intraocular surgery, or intraocular inflammation were obtained by the Konan SP8000 noncontact specular microscope. One observer analyzed these images by using the Konan system and a second observer by using the Bio-Optics Bambi system. Three methods of analyses were used: a fixed-frame method to obtain cell density (for both Konan and Bio-Optics Bambi) and a "dot" (Konan) or "corners" (Bio-Optics Bambi) method to determine morphometric parameters. RESULTS: The cell density determined by the Konan fixed-frame method was significantly higher (157 cells/mm2) than the Bio-Optics Bambi fixed-frame method determination (p<0.0001). However, the difference in cell density, although still statistically significant, was smaller and reversed comparing the Konan fixed-frame method with both Konan dot and Bio-Optics Bambi comers method (-74 cells/mm2, p<0.0001; -55 cells/mm2, p<0.0001, respectively). Small but statistically significant morphometric analyses differences between Konan and Bio-Optics Bambi were seen: cell density, +19 cells/mm2 (p = 0.03); cell area, -3.0 microm2 (p = 0.008); and coefficient of variation, +1.0 (p = 0.003). There was no statistically significant difference between these two methods in the percentage of six-sided cells detected (p = 0.55). CONCLUSION: Cell densities measured by the Konan fixed-frame method were comparable with Konan and Bio-Optics Bambi's morphometric analysis, but not with the Bio-Optics Bambi fixed-frame method. The two morphometric analyses were comparable with minimal or no differences for the parameters that were studied. The Konan SP8000 endothelial image-analysis system may be useful for large-scale clinical trials determining cell loss; its noncontact system has many clinical benefits (including patient comfort, safety, ease of use, and short procedure time) and provides reliable cell-density calculations.

Adolescent↗

[Digital image analysis as an optical tool in biochemistry].

Digital image analysis can be used to assist of complement visual perception. In quantifying light intensities it is superior to the human visual system and therefore is an appropriate and useful tool for research. Using microphotometry as an example the physical bases of digital image analysis are explained and the applications of this measuring technique to biochemical analysis are demonstrated.

Computers↗

Evaluation of skin erythema by use of chromametry and image analysis of digital photographs after intradermal administration of histamine in dogs.

OBJECTIVE: To investigate whether the degree of erythema during an induced erythematous reaction, the histamine skin test reaction, can be assessed objectively by use of chromametry and image analysis of digital photographs. ANIMALS: 9 pet dogs (6 Golden Retrievers and 3 yellow Labrador Retrievers). PROCEDURE: Histamine phosphate was injected intradermally, and erythema of the wheal reaction was evaluated during the hour that followed. This was done by use of clinical scores, chromametry, and image analysis of digital photographs. Method reproducibility was tested for visual evaluation of printouts of digital photographs and for image analysis of the same photographs. RESULTS: The coefficient of variation of the technically derived erythema values was < 10%. The reproducibility of image analysis was high and the range of agreement between observers narrow. Using chromametry, it was not possible to differentiate between various degrees of erythema intensity as visually perceived. In contrast, use of image analysis of digital photographs enabled discrimination of slight erythema from moderate and marked erythema. The dynamics of reaction measured by chromametry followed the clinical observation. CONCLUSIONS AND CLINICAL RELEVANCE: Chromametric values are comparable to those obtained by visual inspection. As the result of standardized conditions, chromametry is preferred over digital photography.

Animals↗

Diabetic retinopathy screening using digital non-mydriatic fundus photography and automated image analysis.

PURPOSE: To investigate the use of automated image analysis for the detection of diabetic retinopathy (DR) in fundus photographs captured with and without pharmacological pupil dilation using a digital non-mydriatic camera. METHODS: A total of 83 patients (165 eyes) with type 1 or type 2 diabetes, representing the full spectrum of DR, were photographed with and without pharmacological pupil dilation using a digital non-mydriatic camera. Two sets of five overlapping, non-stereoscopic, 45-degree field images of each eye were obtained. All images were graded in a masked fashion by two readers according to ETDRS standards and disagreements were settled by an independent adjudicator. Automated detection of red lesions as well as image quality control was made: detection of a single red lesion or insufficient image quality was categorized as possible DR. RESULTS: At patient level, the automated red lesion detection and image quality control combined demonstrated a sensitivity of 89.9% and specificity of 85.7% in detecting DR when used on images captured without pupil dilation, and a sensitivity of 97.0% and specificity of 75.0% when used on images captured with pupil dilation. For moderate non-proliferative or more severe DR the sensitivity was 100% for images captured both with and without pupil dilation. CONCLUSION: Our results demonstrate that the described automated image analysis system, which detects the presence or absence of DR, can be used as a first-step screening tool in DR screening with considerable effectiveness.

Area Under Curve↗