Measurement of epidermal thickness in a patient with psoriasis by computer-supported image analysis

The aim of the present study was to measure full epidermal thickness, stratum corneum thickness, rete length, dermal papilla widening and suprapapillary epidermal thickness in psoriasis patients using a light microscope and computer-supported image analysis. The data obtained were analyzed in terms of patient age, type of psoriasis, total body surface area involvement, scalp and nail involvement, duration of psoriasis, and family history of the disease. The study was conducted on 64 patients and 57 controls whose skin biopsies were examined by light microscopy. The acquired microscopic images were transferred to a computer and measurements were made using image analysis. The skin biopsies, taken from different body areas, were examined for different parameters such as epidermal, corneal and suprapapillary epidermal thickness. The most prominent increase in thickness was detected in the palmar region. Corneal thickness was more pronounced in patients with scalp involvement than in patients without scalp involvement (t = -2.651, P = 0.008). The most prominent increase in rete length was observed in the knees (median: 491 µm, t = 10.117, P = 0.000). The difference in rete length between patients with a positive and a negative family history was significant (t = -3.334, P = 0.03), being 27% greater in psoriasis patients without a family history. The differences in dermal papilla distances among patients were very small. We conclude that microscope-supported thickness measurements provide objective results.

3D reconstruction and quantification of macropores using X-ray computed tomography and image analysis

Axial X-ray Computed tomography (CT) scanning provides a convenient means of recording the three-dimensional form of soil structure. The technique has been used for nearly two decades, but initial development has concentrated on qualitative description of images. More recently, increasing effort has been put into quantifying the geometry and topology of macropores likely to contribute to preferential now in soils. Here we describe a novel technique for tracing connected macropores in the CT scans. After object extraction, three-dimensional mathematical morphological filters are applied to quantify the reconstructed structure. These filters consist of sequences of so-called erosions and/or dilations of a 32-face structuring element to describe object distances and volumes of influence. The tracing and quantification methodologies were tested on a set of undisturbed soil cores collected in a Swiss pre-alpine meadow, where a new earthworm species (Aporrectodea nocturna) was accidentally introduced. Given the reduced number of samples analysed in this study, the results presented only illustrate the potential of the method to reconstruct and quantify macropores. Our results suggest that the introduction of the new species induced very limited chance to the soil structured for example, no difference in total macropore length or mean diameter was observed. However. in the zone colonised by, the new species. individual macropores tended to have a longer average length. be more vertical and be further apart at some depth. Overall, the approach proved well suited to the analysis of the three-dimensional architecture of macropores. It provides a framework for the analysis of complex structures, which are less satisfactorily observed and described using 2D imaging. (C) 2002 Elsevier Science B.V. All rights reserved.

Characterisation of the three-dimensional structure of earthworm burrow systems using image analysis and mathematical morphology

The aim of this work was to exemplify the specific contribution of both two- and three-dimensional (31)) X-ray computed tomography to characterise earthworm burrow systems. To achieve this purpose we used 3D mathematical morphology operators to characterise burrow systems resulting from the activity of an anecic (Aporrectodea noctunia), and an endogeic species (Allolobophora chlorotica), when both species were introduced either separately or together into artificial soil cores. Images of these soil cores were obtained using a medical X-ray tomography scanner. Three-dimensional reconstructions of burrow systems were obtained using a specifically developed segmentation algorithm. To study the differences between burrow systems, a set of classical tools of mathematical morphology (granulometries) were used. So-called granulometries based on different structuring elements clearly separated the different burrow systems. They enabled us to show that burrows made by the anecic species were fatter, longer, more vertical, more continuous but less sinuous than burrows of the endogeic species. The granulometry transform of the soil matrix showed that burrows made by A. nocturna were more evenly distributed than those of A. chlorotica. Although a good discrimination was possible when only one species was introduced into the soil cores, it was not possible to separate burrows of the two species from each other in cases where species were introduced into the same soil core. This limitation, partly due to the insufficient spatial resolution of the medical scanner, precluded the use of the morphological operators to study putative interactions between the two species.

In-plane displacement and strain image analysis

Measurements in civil engineering load tests usually require considerable time and complex procedures. Therefore, measurements are usually constrained by the number of sensors resulting in a restricted monitored area. Image processing analysis is an alternative way that enables the measurement of the complete area of interest with a simple and effective setup. In this article photo sequences taken during load displacement tests were captured by a digital camera and processed with image correlation algorithms. Three different image processing algorithms were used with real images taken from tests using specimens of PVC and Plexiglas. The data obtained from the image processing algorithms were also compared with the data from physical sensors. A complete displacement and strain map were obtained. Results show that the accuracy of the measurements obtained by photogrammetry is equivalent to that from the physical sensors but with much less equipment and fewer setup requirements. © 2015Computer-Aided Civil and Infrastructure Engineering.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

Computational Techniques for Spectral Image Analysis

Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.

Example Based Image Analysis and Synthesis

Image analysis and graphics synthesis can be achieved with learning techniques using directly image examples without physically-based, 3D models. In our technique: -- the mapping from novel images to a vector of "pose" and "expression" parameters can be learned from a small set of example images using a function approximation technique that we call an analysis network; -- the inverse mapping from input "pose" and "expression" parameters to output images can be synthesized from a small set of example images and used to produce new images using a similar synthesis network. The techniques described here have several applications in computer graphics, special effects, interactive multimedia and very low bandwidth teleconferencing.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Petroleum well drilling monitoring through cutting image analysis and artificial intelligence techniques

Petroleum well drilling monitoring has become an important tool for detecting and preventing problems during the well drilling process. In this paper, we propose to assist the drilling process by analyzing the cutting images at the vibrating shake shaker, in which different concentrations of cuttings can indicate possible problems, such as the collapse of the well borehole walls. In such a way, we present here an innovative computer vision system composed by a real time cutting volume estimator addressed by support vector regression. As far we know, we are the first to propose the petroleum well drilling monitoring by cutting image analysis. We also applied a collection of supervised classifiers for cutting volume classification. (C) 2010 Elsevier Ltd. All rights reserved.

Computer-assisted analysis of cell proliferation markers in oral lesions

Abnormalities in any component of the cell cycle regulatory machine may result in oral. cancer, and markers of cell proliferation have been used to determine the prognosis of tumor progression. The aim of this study was to determine whether silver-stained nucleolar organizer region (AgNOR) and Ki-67 measurements could improve the assessment of growth rates in oral lesions. Eighty-three oral biopsies were studied, 20 of which were classified as fibrous inflammatory hyperplasia (FIH), 40 as leukoplakia (LKP) and 23 as oral. squamous cell carcinoma (OSCC). Within the LKP group, 22 out of 29 biopsies were diagnosed as non-dysplastic leukoplakia (LK) and 18 as dysplastic teukoptakia (DLK), presenting discrete, moderate and severe dysplasia. Ki-67 immunotabeting of the lesions increased steadily in the following order: FIH, DLK, LK and OSCC, indicating that Ki-67 is a good marker for predicting the protiferative fraction among benign, premalignant and malignant oral lesions. The median values of AgNOR parameters indicate that the morphometric index gives better results regarding the proliferative rate than the numerical one. A series of linear regressions between AgNOR parameters and Ki-67 showed positive associations. We conclude that a combination of Ki-67 and morphometric AgNOR analyses could be used as an aid in the determination of the protiferative status of oral epithelial. cells in oral cancer. (C) 2007 Elsevier GmbH. All rights reserved.

Computer-assisted analysis of p53 and PCNA expression in oral lesions infected with human papillomavirus

OBJECTIVE: To carry out a retrospective study to determine whether human papillomavirus (HPV) infection and immunohistochemical expression of p53 and proliferating cell nuclear antigen (PCNA) are related to the risk of oral cancer. STUDY DESIGN: Fifty-seven oral biopsies, consisting of 30 oral squamous papillomas (OSPs) and 27 oral squamous cell carcinomas (OSCCs) were tested for the presence of HPV 6/11 and 16/18 by in situ hybridization using catalyzed signal amplification and in situ hybridization. p53 And PCNA expression was analyzed by immunohistochemistry and evaluated quantitatively by image analysis. RESULTS: Nineteen of the 57 oral lesions (33.3%) were positive for HPV. HPV 6/11 was found in 6 of 30 (20%) OSPs and 1 of 27 (3.7%) OSCCs. HPV 16/18 was found in 10 of 27 (37%) OSCCs and 2 of 30 (6.7%) OSPs. Sixteen of the 19 HPV-positive cases (84.2%) were p53 negative; 5 (9%) were HPV 6/11 and 11 (19%) HPV 16/18, with an inverse correlation between the presence of HPV DNA and p53 expression (P=.017, P < .05). PCNA expression appeared in 18 (94.7%) of HPV positive cases, showing that HPV 16/18 was associated with intensity of PCNA expression and with OSCCs (P=.037, P < .05). CONCLUSION: Quantitative evaluation of p53 by image analysis showed an inverse correlation between p53 expression and HPV presence, suggesting protein degradation. Image analysis also demonstrated that PCNA expression was more intense in HPV DNA 16/18 OSCCs. These findings suggest involvement of high-risk HPV types in oral carcinogenesis.

Morphometric study by image analysis of Ag-stained nucleoli in thyroids bearing proliferating lesions

The Ag-NOR staining technique and image analysis were used to evaluate morphological parameters (area, perimeter and axis ratio) in nucleoli from normal thyroids and from thyroids bearing proliferating lesions (carcinomas, adenomas and hyperplasias). Regions with normal appearance located close to adenomatous and carcinomatous regions, in the thyroid of every patient, were also analyzed for comparison with the respective pathological regions and with normal thyroids. Statistical analysis of data for the nucleolar area and perimeter allowed the separation of adenomas and carcinomas from hyperplasias and normal tissue but not the two components in each of these two groups. However, if we look at the numbers, a sequence of increasing nucleolar mean areas in the order: normal, hyperplasia, adenoma and carcinoma may be observed, indicating the sequence of increasing rRNA requirements in these different kinds of cells. The axis ratio that denotes the nucleolar shape (round or oblong) did not show significant differences among tissues, suggesting that shape is not important in the characterization of these pathologies. Differences in nucleolar areas and perimeter between normal and affected regions from each patient were statistically significant for adenomas and carcinomas. When these normal regions were compared with the normal thyroids, significant differences were not obtained in the three evaluated parameters. The observations and their importance for histopathological diagnosis are discussed.