Breast tissue classification using x-ray scattering measurements and multivariate data analysis

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Ryan, Elaine A; Farquharson, Michael J [School of Allied Health Sciences, City University, Charterhouse Square, London EC1M 6PA (United Kingdom)

2007-11-21

This study utilized two radiation scatter interactions in order to differentiate malignant from non-malignant breast tissue. These two interactions were Compton scatter, used to measure the electron density of the tissues, and coherent scatter to obtain a measure of structure. Measurements of these parameters were made using a laboratory experimental set-up comprising an x-ray tube and HPGe detector. The breast tissue samples investigated comprise five different tissue classifications: adipose, malignancy, fibroadenoma, normal fibrous tissue and tissue that had undergone fibrocystic change. The coherent scatter spectra were analysed using a peak fitting routine, and a technique involving multivariate analysis was used to combine the peak fitted scatter profile spectra and the electron density values into a tissue classification model. The number of variables used in the model was refined by finding the sensitivity and specificity of each model and concentrating on differentiating between two tissues at a time. The best model that was formulated had a sensitivity of 54% and a specificity of 100%.

Surgical Masculinization of the Breast: Clinical Classification and Surgical Procedures.

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Cardenas-Camarena, Lazaro; Dorado, Carlos; Guerrero, Maria Teresa; Nava, Rosa

2017-06-01

Aesthetic breast area improvements for gynecomastia and gender dysphoria patients who seek a more masculine appearance have increased recently. We present our clinical experience in breast masculinization and a classification for these patients. From July 2003 to May 2014, 68 patients seeking a more masculine thorax underwent surgery. They were divided into five groups depending on three factors: excess fatty tissue, breast tissue, and skin. A specific surgical treatment was assigned according to each group. The surgical treatments included thoracic liposuction, subcutaneous mastectomy, periareolar skin resection in one or two stages, and mastectomy with a nipple areola complex graft. The evaluation was performed 6 months after surgery to determine the degree of satisfaction and presence of complications. Surgery was performed on a total of 68 patients, 45 male and 22 female, with ages ranging from 18 to 49 years, and an average age of 33 years. Liposuction alone was performed on five patients; subcutaneous mastectomy was performed on eight patients; subcutaneous mastectomy combined with liposuction was performed on 27 patients; periareolar skin resection was performed on 11 patients; and mastectomy with NAC free grafts was performed on 16 patients. The surgical procedure satisfied 94% of the patients, with very few complications. All patients who wish to obtain a masculine breast shape should be treated with only one objective regardless patient's gender: to obtain a masculine thorax. We recommend a simple mammary gland classification for determining the best surgical treatment for these patients LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Subcutaneous adipose tissue classification

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A. Sbarbati

2010-11-01

Full Text Available The developments in the technologies based on the use of autologous adipose tissue attracted attention to minor depots as possible sampling areas. Some of those depots have never been studied in detail. The present study was performed on subcutaneous adipose depots sampled in different areas with the aim of explaining their morphology, particularly as far as regards stem niches. The results demonstrated that three different types of white adipose tissue (WAT can be differentiated on the basis of structural and ultrastructural features: deposit WAT (dWAT, structural WAT (sWAT and fibrous WAT (fWAT. dWAT can be found essentially in large fatty depots in the abdominal area (periumbilical. In the dWAT, cells are tightly packed and linked by a weak net of isolated collagen fibers. Collagenic components are very poor, cells are large and few blood vessels are present. The deep portion appears more fibrous then the superficial one. The microcirculation is formed by thin walled capillaries with rare stem niches. Reinforcement pericyte elements are rarely evident. The sWAT is more stromal; it is located in some areas in the limbs and in the hips. The stroma is fairly well represented, with a good vascularity and adequate staminality. Cells are wrapped by a basket of collagen fibers. The fatty depots of the knees and of the trochanteric areas have quite loose meshes. The fWAT has a noteworthy fibrous component and can be found in areas where a severe mechanic stress occurs. Adipocytes have an individual thick fibrous shell. In conclusion, the present study demonstrates evident differences among subcutaneous WAT deposits, thus suggesting that in regenerative procedures based on autologous adipose tissues the sampling area should not be randomly chosen, but it should be oriented by evidence based evaluations. The structural peculiarities of the sWAT, and particularly of its microcirculation, suggest that it could represent a privileged source for

Tissue classification and segmentation of pressure injuries using convolutional neural networks.

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Zahia, Sofia; Sierra-Sosa, Daniel; Garcia-Zapirain, Begonya; Elmaghraby, Adel

2018-06-01

This paper presents a new approach for automatic tissue classification in pressure injuries. These wounds are localized skin damages which need frequent diagnosis and treatment. Therefore, a reliable and accurate systems for segmentation and tissue type identification are needed in order to achieve better treatment results. Our proposed system is based on a Convolutional Neural Network (CNN) devoted to performing optimized segmentation of the different tissue types present in pressure injuries (granulation, slough, and necrotic tissues). A preprocessing step removes the flash light and creates a set of 5x5 sub-images which are used as input for the CNN network. The network output will classify every sub-image of the validation set into one of the three classes studied. The metrics used to evaluate our approach show an overall average classification accuracy of 92.01%, an average total weighted Dice Similarity Coefficient of 91.38%, and an average precision per class of 97.31% for granulation tissue, 96.59% for necrotic tissue, and 77.90% for slough tissue. Our system has been proven to make recognition of complicated structures in biomedical images feasible. Copyright © 2018 Elsevier B.V. All rights reserved.

Chronic radiation effects on dental hard tissue (''radiation carries''). Classification and therapeutic strategies

International Nuclear Information System (INIS)

Groetz, K.A.; Brahm, R.; Al-Nawas, B.; Wagner, W.; Riesenbeck, D.; Willich, N.; Seegenschmiedt, M.H.

2001-01-01

Objectives: Since the first description of rapid destruction of dental hard tissues following head and neck radiotherapy 80 years ago, 'radiation caries' is an established clinical finding. The internationally accepted clinical evaluation score RTOG/EORTC however is lacking a classification of this frequent radiogenic alteration. Material and Methods: Medical records, data and images of radiation effects on the teeth of more than 1,500 patients, who underwent periradiotherapeutic care, were analyzed. Macroscopic alterations regarding the grade of late lesions of tooth crowns were used for a classification into 4 grades according to the RTOG/EORTC guidelines. Results: No early radiation effects were found by macroscopic inspection. In the first 90 days following radiotherapy 1/3 of the patients complained of reversible hypersensitivity, which may be related to a temporary hyperemia of the pulp. It was possible to classify radiation caries as a late radiation effect on a graded scale as known from RTOG/EORTC for other organ systems. This is a prerequisite for the integration of radiation caries into the international nomenclature of the RTOG/EORTC classification. Conclusions: The documentation of early radiation effects on dental hard tissues seems to be neglectable. On the other hand the documentation of late radiation effects has a high clinical impact. The identification of an initial lesion at the high-risk areas of the neck and incisal part of the tooth can lead to a successful therapy as a major prerequisite for orofacial rehabilitation. An internationally standardized documentation is a basis for the evaluation of the side effects of radiooncotic therapy as well as the effectiveness of protective and supportive procedures. (orig.) [de

A study for Unsafe Act classification under crew interaction during procedure-driven operation

International Nuclear Information System (INIS)

Choi, Sun Yeong; Park, Jinkyun; Kim, Yochan; Kim, Seunghwan; Jung, Wondea

2016-01-01

Highlights: • The procedure driven operation was divided into four stages by considering the crew relations such as instructions and responses. • Ten patterns of UA occurrence paths and the related operators per path were identified. • The UA type classification scheme was proposed based on the ten patterns of UA occurrence paths. • A case study to implement the UA type classification and to define the related operators per UA was performed. • The UA type classification scheme can be practical in that it prevents bias by subjective judgment. - Abstract: In this study, a method for UA (Unsafe Act) classification under a simulated procedure driven operation was proposed. To this end, a procedure driven operation was divided into four stages by considering the crew relations such as instructions and responses. Based on the four stages of a procedure driven operation, ten patterns of UA occurrence paths and the related operators per path were identified. From the ten types of UA occurrence paths including related operators, it is practicable to trace when and by whom a UA is initiated during a procedure driven operation, and the interaction or causality among the crew after the UA is initiated. Therefore, the types of UAs were classified into ‘Instruction UA’, ‘Reporting UA’, and ‘Execution UA’ by considering the initiation time and initiator of UA. A case study to implement the UA type classification and to define the related operators per UA was performed with the ISLOCA scenario simulator training data. The UA classification scheme proposed in this paper can be practical in that it does not require expertise relatively in a human performance analysis and it prevents bias by subjective judgment because it is based on an observation-based approach to exclude subjective judgment.

MRI Brain Images Healthy and Pathological Tissues Classification with the Aid of Improved Particle Swarm Optimization and Neural Network

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Sheejakumari, V.; Sankara Gomathi, B.

2015-01-01

The advantages of magnetic resonance imaging (MRI) over other diagnostic imaging modalities are its higher spatial resolution and its better discrimination of soft tissue. In the previous tissues classification method, the healthy and pathological tissues are classified from the MRI brain images using HGANN. But the method lacks sensitivity and accuracy measures. The classification method is inadequate in its performance in terms of these two parameters. So, to avoid these drawbacks, a new classification method is proposed in this paper. Here, new tissues classification method is proposed with improved particle swarm optimization (IPSO) technique to classify the healthy and pathological tissues from the given MRI images. Our proposed classification method includes the same four stages, namely, tissue segmentation, feature extraction, heuristic feature selection, and tissue classification. The method is implemented and the results are analyzed in terms of various statistical performance measures. The results show the effectiveness of the proposed classification method in classifying the tissues and the achieved improvement in sensitivity and accuracy measures. Furthermore, the performance of the proposed technique is evaluated by comparing it with the other segmentation methods. PMID:25977706

Implementation of several mathematical algorithms to breast tissue density classification

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Quintana, C.; Redondo, M.; Tirao, G.

2014-02-01

The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.

Combining extreme learning machines using support vector machines for breast tissue classification.

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Daliri, Mohammad Reza

2015-01-01

In this paper, we present a new approach for breast tissue classification using the features derived from electrical impedance spectroscopy. This method is composed of a feature extraction method, feature selection phase and a classification step. The feature extraction phase derives the features from the electrical impedance spectra. The extracted features consist of the impedivity at zero frequency (I0), the phase angle at 500 KHz, the high-frequency slope of phase angle, the impedance distance between spectral ends, the area under spectrum, the normalised area, the maximum of the spectrum, the distance between impedivity at I0 and the real part of the maximum frequency point and the length of the spectral curve. The system uses the information theoretic criterion as a strategy for feature selection and the combining extreme learning machines (ELMs) for the classification phase. The results of several ELMs are combined using the support vector machines classifier, and the result of classification is reported as a measure of the performance of the system. The results indicate that the proposed system achieves high accuracy in classification of breast tissues using the electrical impedance spectroscopy.

Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections.

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Kuepper, Claus; Kallenbach-Thieltges, Angela; Juette, Hendrik; Tannapfel, Andrea; Großerueschkamp, Frederik; Gerwert, Klaus

2018-05-16

A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

The method of diagnosis and classification of the gingival line defects of the teeth hard tissues

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Olena Bulbuk

2017-06-01

Full Text Available For solving the problem of diagnosis and treatment of hard tissue defects the significant role belongs to the choice of tactics for dental treatment of hard tissue defects located in the gingival line of any tooth. This work aims to study the problems of diagnosis and classification of gingival line defects of the teeth hard tissues. That will contribute to the objectification of differentiated diagnostic and therapeutic approaches in the dental treatment of various clinical variants of these defects localization. The objective of the study – is to develop the anatomical-functional classification for differentiated estimation of hard tissue defects in the gingival part, as the basis for the application of differential diagnostic-therapeutic approaches to the dental treatment of hard tissue defects disposed in the gingival part of any tooth. Materials and methods of investigation: There was conducted the examination of 48 patients with hard tissue defects located in the gingival part of any tooth. To assess the magnitude of gingival line destruction the periodontal probe and X-ray examination were used. Results. The result of the performed research the classification of the gingival line defects of the hard tissues was offered using exponent power. The value of this indicator is equal to an integer number expressed in millimeters of distance from the epithelial attachment to the cavity’s bottom of defect. Conclusions. The proposed classification fills an obvious gap in academic representations about hard tissue defects located in the gingival part of any tooth. Also it offers the prospects of consensus on differentiated diagnostic-therapeutic approaches in different clinical variants of location.  This classification builds methodological “bridge of continuity” between therapeutic and prosthetic dentistry in the field of treatment of the gingival line defects of dental hard tissues.

Automating the expert consensus paradigm for robust lung tissue classification

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Rajagopalan, Srinivasan; Karwoski, Ronald A.; Raghunath, Sushravya; Bartholmai, Brian J.; Robb, Richard A.

2012-03-01

Clinicians confirm the efficacy of dynamic multidisciplinary interactions in diagnosing Lung disease/wellness from CT scans. However, routine clinical practice cannot readily accomodate such interactions. Current schemes for automating lung tissue classification are based on a single elusive disease differentiating metric; this undermines their reliability in routine diagnosis. We propose a computational workflow that uses a collection (#: 15) of probability density functions (pdf)-based similarity metrics to automatically cluster pattern-specific (#patterns: 5) volumes of interest (#VOI: 976) extracted from the lung CT scans of 14 patients. The resultant clusters are refined for intra-partition compactness and subsequently aggregated into a super cluster using a cluster ensemble technique. The super clusters were validated against the consensus agreement of four clinical experts. The aggregations correlated strongly with expert consensus. By effectively mimicking the expertise of physicians, the proposed workflow could make automation of lung tissue classification a clinical reality.

A classification of the mechanisms producing pathological tissue changes.

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Grippo, John O; Oh, Daniel S

2013-05-01

The objectives are to present a classification of mechanisms which can produce pathological changes in body tissues and fluids, as well as to clarify and define the term biocorrosion, which has had a singular use in engineering. Considering the emerging field of biomedical engineering, it is essential to use precise definitions in the lexicons of engineering, bioengineering and related sciences such as medicine, dentistry and veterinary medicine. The mechanisms of stress, friction and biocorrosion and their pathological effects on tissues are described. Biocorrosion refers to the chemical, biochemical and electrochemical changes by degradation or induced growth of living body tissues and fluids. Various agents which can affect living tissues causing biocorrosion are enumerated which support the necessity and justify the use of this encompassing and more precise definition of biocorrosion. A distinction is made between the mechanisms of corrosion and biocorrosion.

A Dirichlet process mixture model for brain MRI tissue classification.

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Ferreira da Silva, Adelino R

2007-04-01

Accurate classification of magnetic resonance images according to tissue type or region of interest has become a critical requirement in diagnosis, treatment planning, and cognitive neuroscience. Several authors have shown that finite mixture models give excellent results in the automated segmentation of MR images of the human normal brain. However, performance and robustness of finite mixture models deteriorate when the models have to deal with a variety of anatomical structures. In this paper, we propose a nonparametric Bayesian model for tissue classification of MR images of the brain. The model, known as Dirichlet process mixture model, uses Dirichlet process priors to overcome the limitations of current parametric finite mixture models. To validate the accuracy and robustness of our method we present the results of experiments carried out on simulated MR brain scans, as well as on real MR image data. The results are compared with similar results from other well-known MRI segmentation methods.

75 FR 68972 - Medical Devices; General and Plastic Surgery Devices; Classification of Tissue Adhesive With...

Science.gov (United States)

2010-11-10

.... FDA-2010-N-0512] Medical Devices; General and Plastic Surgery Devices; Classification of Tissue... running to unintended areas, etc. B. Wound dehiscence C. Adverse tissue reaction and chemical burns D..., Clinical Studies, Labeling. Adverse tissue reaction and chemical Biocompatibility Animal burns. Testing...

Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT (Conference Presentation)

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Yao, Xinwen; Gan, Yu; Chang, Ernest W.; Hibshoosh, Hanina; Feldman, Sheldon; Hendon, Christine P.

2017-02-01

We employed a home-built ultrahigh resolution (UHR) OCT system at 800nm to image human breast cancer sample ex vivo. The system has an axial resolution of 2.72µm and a lateral resolution of 5.52µm with an extended imaging range of 1.78mm. Over 900 UHR OCT volumes were generated on specimens from 23 breast cancer cases. With better spatial resolution, detailed structures in the breast tissue were better defined. Different types of breast cancer as well as healthy breast tissue can be well delineated from the UHR OCT images. To quantitatively evaluate the advantages of UHR OCT imaging of breast cancer, features derived from OCT intensity images were used as inputs to a machine learning model, the relevance vector machine. A trained machine learning model was employed to evaluate the performance of tissue classification based on UHR OCT images for differentiating tissue types in the breast samples, including adipose tissue, healthy stroma and cancerous region. For adipose tissue, grid-based local features were extracted from OCT intensity data, including standard deviation, entropy, and homogeneity. We showed that it was possible to enhance the classification performance on distinguishing fat tissue from non-fat tissue by using the UHR images when compared with the results based on OCT images from a commercial 1300 nm OCT system. For invasive ductal carcinoma (IDC) and normal stroma differentiation, the classification was based on frame-based features that portray signal penetration depth and tissue reflectivity. The confusing matrix indicated a sensitivity of 97.5% and a sensitivity of 77.8%.

Support vector machine classification and validation of cancer tissue samples using microarray expression data.

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Furey, T S; Cristianini, N; Duffy, N; Bednarski, D W; Schummer, M; Haussler, D

2000-10-01

DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results. We demonstrate the method in detail on samples consisting of ovarian cancer tissues, normal ovarian tissues, and other normal tissues. The dataset consists of expression experiment results for 97,802 cDNAs for each tissue. As a result of computational analysis, a tissue sample is discovered and confirmed to be wrongly labeled. Upon correction of this mistake and the removal of an outlier, perfect classification of tissues is achieved, but not with high confidence. We identify and analyse a subset of genes from the ovarian dataset whose expression is highly differentiated between the types of tissues. To show robustness of the SVM method, two previously published datasets from other types of tissues or cells are analysed. The results are comparable to those previously obtained. We show that other machine learning methods also perform comparably to the SVM on many of those datasets. The SVM software is available at http://www.cs. columbia.edu/ approximately bgrundy/svm.

Classification of fibroglandular tissue distribution in the breast based on radiotherapy planning CT

International Nuclear Information System (INIS)

Juneja, Prabhjot; Evans, Philip; Windridge, David; Harris, Emma

2016-01-01

Accurate segmentation of breast tissues is required for a number of applications such as model based deformable registration in breast radiotherapy. The accuracy of breast tissue segmentation is affected by the spatial distribution (or pattern) of fibroglandular tissue (FT). The goal of this study was to develop and evaluate texture features, determined from planning computed tomography (CT) data, to classify the spatial distribution of FT in the breast. Planning CT data of 23 patients were evaluated in this study. Texture features were derived from the radial glandular fraction (RGF), which described the distribution of FT within three breast regions (posterior, middle, and anterior). Using visual assessment, experts grouped patients according to FT spatial distribution: sparse or non-sparse. Differences in the features between the two groups were investigated using the Wilcoxon rank test. Classification performance of the features was evaluated for a range of support vector machine (SVM) classifiers. Experts found eight patients and 15 patients had sparse and non-sparse spatial distribution of FT, respectively. A large proportion of features (>9 of 13) from the individual breast regions had significant differences (p <0.05) between the sparse and non-sparse group. The features from middle region had most significant differences and gave the highest classification accuracy for all the SVM kernels investigated. Overall, the features from middle breast region achieved highest accuracy (91 %) with the linear SVM kernel. This study found that features based on radial glandular fraction provide a means for discriminating between fibroglandular tissue distributions and could achieve a classification accuracy of 91 %

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration.

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Young Kim, Eun; Johnson, Hans J

2013-01-01

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

Cell-based product classification procedure: What can be done differently to improve decisions on borderline products?

Science.gov (United States)

Izeta, Ander; Herrera, Concha; Mata, Rosario; Astori, Giuseppe; Giordano, Rosaria; Hernández, Carmen; Leyva, Laura; Arias, Salvador; Oyonarte, Salvador; Carmona, Gloria; Cuende, Natividad

2016-07-01

In June 2015, European Medicines Agency/Committee for Advanced Therapies (CAT) released the new version of the reflection paper on classification of advanced therapy medicinal products (ATMPs) established to address questions of borderline cases in which classification of a product based on genes, cells or tissues is unclear. The paper shows CAT's understanding of substantial manipulation and essential function(s) criteria that define the legal scope of cell-based medicinal products. This article aims to define the authors' viewpoint on the reflection paper. ATMP classification has intrinsic weaknesses derived from the lack of clarity of the evolving concepts of substantial manipulation and essential function(s) as stated in the EU Regulation, leading to the risk of differing interpretations and misclassification. This might result in the broadening of ATMP scope at the expense of other products such as cell/tissue transplants and blood products, or even putting some present and future clinical practice at risk of being classified as ATMP. Because of the major organizational, economic and regulatory implications of product classification, we advocate for increased interaction between CAT and competent authorities (CAs) for medicines, blood and blood components and tissues and cells or for the creation of working groups including representatives of all parties as recently suggested by several CAs. Copyright © 2016 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Efficacy of hidden markov model over support vector machine on multiclass classification of healthy and cancerous cervical tissues

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Mukhopadhyay, Sabyasachi; Kurmi, Indrajit; Pratiher, Sawon; Mukherjee, Sukanya; Barman, Ritwik; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2018-02-01

In this paper, a comparative study between SVM and HMM has been carried out for multiclass classification of cervical healthy and cancerous tissues. In our study, the HMM methodology is more promising to produce higher accuracy in classification.

The differentiation of malignant and benign human breast tissue at surgical margins and biopsy using x-ray interaction data and Bayesian classification

International Nuclear Information System (INIS)

Mersov, A.; Mersov, G.; Al-Ebraheem, A.; Cornacchi, S.; Gohla, G.; Lovrics, P.; Farquharson, M.J.

2014-01-01

Worldwide, about 1.3 million women are diagnosed with breast cancer annually with an estimated 465,000 deaths. Accordingly, there is a need for high accuracy and speed in diagnosis of lesions suspected of being cancerous. This study assesses the interaction data collected from low energy x-rays within breast tissue samples. Trace element concentrations are assessed using x-ray fluorescence, as well as electron density, and molecular structure which are examined using incoherent and coherent scatter, respectively. Our work to date has shown that such data can provide a quantitative measure of certain tissue characterising parameters and hence, through appropriate modelling, could be used to classify samples for uses such as surgical margin detection and biopsy examination. The parameters used in this study for comparing the normal and tumour tissue sample populations are: levels of elements Ca, Cu, Fe, Br, Zn, Rb, K; the area, FWHM and amplitude from peaks fitted to the coherent scatter profile that are associated with fat, fibre and water content; the ratio of the Compton and coherent scatter peak area, FWHM and amplitude from the incoherent scatter profile. The novelty of the approach to this work lies in the fact that the classification process does not rely on one source of data but combines several measurements, the data from which in this application are modelled using a method based on Bayesian classification. The reliability of the classifications was assessed by its application to diagnostically known data that was not itself included in the thresholds determination. The results of the classification of over 70 breast tissue samples will be presented in this study. Bayesian modelling was carried out using selected significant parameters for classification resulting in 71% of normal tissue samples (n=35) and 66% of tumour tissue samples (n=35) being correctly classified when using all the samples. Bayesian classification using the same variables on all

Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

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Richard eBeare

2016-03-01

Full Text Available Measuring the distribution of brain tissue types (tissue classification in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation, which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF, hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks’ gestation acquired at 30 weeks’ corrected gestational age (n= 5, coronal T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5 and axial T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5. The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR group, consisted of T2-weighted images of preterm infants (born <30 weeks’ gestation acquired shortly after birth (n= 12, preterm infants acquired at term-equivalent age (n= 12, and healthy term-born infants (born ≥38 weeks’ gestation acquired within the first nine days of life (n= 12. For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for

Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2013-01-01

their power in this field. Two important issues of bag-of-feature strategy for tissue classification are investigated in this paper: the visual vocabulary learning and weighting, which are always considered independently in traditional methods by neglecting

Breast tissue classification in digital tomosynthesis images based on global gradient minimization and texture features

Science.gov (United States)

Qin, Xulei; Lu, Guolan; Sechopoulos, Ioannis; Fei, Baowei

2014-03-01

Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images.

Automated classification and visualization of healthy and pathological dental tissues based on near-infrared hyper-spectral imaging

Science.gov (United States)

Usenik, Peter; Bürmen, Miran; Vrtovec, Tomaž; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan

2011-03-01

Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots which are difficult to diagnose. If detected early enough, such demineralization can be arrested and reversed by non-surgical means through well established dental treatments (fluoride therapy, anti-bacterial therapy, low intensity laser irradiation). Near-infrared (NIR) hyper-spectral imaging is a new promising technique for early detection of demineralization based on distinct spectral features of healthy and pathological dental tissues. In this study, we apply NIR hyper-spectral imaging to classify and visualize healthy and pathological dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized areas. For this purpose, a standardized teeth database was constructed consisting of 12 extracted human teeth with different degrees of natural dental lesions imaged by NIR hyper-spectral system, X-ray and digital color camera. The color and X-ray images of teeth were presented to a clinical expert for localization and classification of the dental tissues, thereby obtaining the gold standard. Principal component analysis was used for multivariate local modeling of healthy and pathological dental tissues. Finally, the dental tissues were classified by employing multiple discriminant analysis. High agreement was observed between the resulting classification and the gold standard with the classification sensitivity and specificity exceeding 85 % and 97 %, respectively. This study demonstrates that NIR hyper-spectral imaging has considerable diagnostic potential for imaging hard dental tissues.

Biased visualization of hypoperfused tissue by computed tomography due to short imaging duration: improved classification by image down-sampling and vascular models

Energy Technology Data Exchange (ETDEWEB)

Mikkelsen, Irene Klaerke; Ribe, Lars Riisgaard; Bekke, Susanne Lise; Tietze, Anna; Oestergaard, Leif; Mouridsen, Kim [Aarhus University Hospital, Center of Functionally Integrative Neuroscience, Aarhus C (Denmark); Jones, P.S.; Alawneh, Josef [University of Cambridge, Department of Clinical Neurosciences, Cambridge (United Kingdom); Puig, Josep; Pedraza, Salva [Dr. Josep Trueta Girona University Hospitals, Department of Radiology, Girona Biomedical Research Institute, Girona (Spain); Gillard, Jonathan H. [University of Cambridge, Department of Radiology, Cambridge (United Kingdom); Warburton, Elisabeth A. [Cambrigde University Hospitals, Addenbrooke, Stroke Unit, Cambridge (United Kingdom); Baron, Jean-Claude [University of Cambridge, Department of Clinical Neurosciences, Cambridge (United Kingdom); Centre Hospitalier Sainte Anne, INSERM U894, Paris (France)

2015-07-15

Lesion detection in acute stroke by computed-tomography perfusion (CTP) can be affected by incomplete bolus coverage in veins and hypoperfused tissue, so-called bolus truncation (BT), and low contrast-to-noise ratio (CNR). We examined the BT-frequency and hypothesized that image down-sampling and a vascular model (VM) for perfusion calculation would improve normo- and hypoperfused tissue classification. CTP datasets from 40 acute stroke patients were retrospectively analysed for BT. In 16 patients with hypoperfused tissue but no BT, repeated 2-by-2 image down-sampling and uniform filtering was performed, comparing CNR to perfusion-MRI levels and tissue classification to that of unprocessed data. By simulating reduced scan duration, the minimum scan-duration at which estimated lesion volumes came within 10 % of their true volume was compared for VM and state-of-the-art algorithms. BT in veins and hypoperfused tissue was observed in 9/40 (22.5 %) and 17/40 patients (42.5 %), respectively. Down-sampling to 128 x 128 resolution yielded CNR comparable to MR data and improved tissue classification (p = 0.0069). VM reduced minimum scan duration, providing reliable maps of cerebral blood flow and mean transit time: 5 s (p = 0.03) and 7 s (p < 0.0001), respectively. BT is not uncommon in stroke CTP with 40-s scan duration. Applying image down-sampling and VM improve tissue classification. (orig.)

Biased visualization of hypoperfused tissue by computed tomography due to short imaging duration: improved classification by image down-sampling and vascular models

International Nuclear Information System (INIS)

Mikkelsen, Irene Klaerke; Ribe, Lars Riisgaard; Bekke, Susanne Lise; Tietze, Anna; Oestergaard, Leif; Mouridsen, Kim; Jones, P.S.; Alawneh, Josef; Puig, Josep; Pedraza, Salva; Gillard, Jonathan H.; Warburton, Elisabeth A.; Baron, Jean-Claude

2015-01-01

Lesion detection in acute stroke by computed-tomography perfusion (CTP) can be affected by incomplete bolus coverage in veins and hypoperfused tissue, so-called bolus truncation (BT), and low contrast-to-noise ratio (CNR). We examined the BT-frequency and hypothesized that image down-sampling and a vascular model (VM) for perfusion calculation would improve normo- and hypoperfused tissue classification. CTP datasets from 40 acute stroke patients were retrospectively analysed for BT. In 16 patients with hypoperfused tissue but no BT, repeated 2-by-2 image down-sampling and uniform filtering was performed, comparing CNR to perfusion-MRI levels and tissue classification to that of unprocessed data. By simulating reduced scan duration, the minimum scan-duration at which estimated lesion volumes came within 10 % of their true volume was compared for VM and state-of-the-art algorithms. BT in veins and hypoperfused tissue was observed in 9/40 (22.5 %) and 17/40 patients (42.5 %), respectively. Down-sampling to 128 x 128 resolution yielded CNR comparable to MR data and improved tissue classification (p = 0.0069). VM reduced minimum scan duration, providing reliable maps of cerebral blood flow and mean transit time: 5 s (p = 0.03) and 7 s (p < 0.0001), respectively. BT is not uncommon in stroke CTP with 40-s scan duration. Applying image down-sampling and VM improve tissue classification. (orig.)

A methodological approach to assessing alveolar ridge preservation procedures in humans: soft tissue profile.

Science.gov (United States)

Vanhoutte, Vanessa; Rompen, Eric; Lecloux, Geoffrey; Rues, Stefan; Schmitter, Marc; Lambert, France

2014-03-01

The aesthetic results of implant restoration in the anterior maxilla are particularly related to the soft tissue profile. Although socket preservation techniques appear to reduce bone remodelling after tooth extraction, there is still few investigations assessing the external soft tissue profile after such procedures. The goal of this study was to describe an accurate technique to evaluate soft tissue contour changes after performing socket preservation procedures. The secondary objective was to apply the newly developed measuring method to a specific socket preservation using a "saddled" connective tissue graft combined with the insertion of slowly resorbable biomaterials into the socket. A total of 14 patients needing tooth replacement in the aesthetic region were included to receive a socket preservation procedure using a connective tissue graft. Impressions were taken before the tooth extraction (baseline) and at 2, 4, and 12 weeks after the procedure. The corresponding plaster casts were scanned, and the evolution of the soft tissue profile in relation to the baseline situation was assessed using imaging software. The measuring technique allowed assessing the soft tissue profiles accurately at different levels of the alveolar process. The insertion of a saddled connective tissue appeared to compensate for the horizontal and vertical bone remodelling after a socket preservation procedure in most regions of the alveolar crest. After 12 weeks, the only significant change was located in the more cervical and central region of the alveolar process and reached a median drop of 0.62 mm from baseline. Within the limitations of this study, we found that a saddled connective tissue graft combined with a socket preservation procedure could almost completely counteract the bone remodelling in terms of the external soft tissue profile. The minor changes found in the cervical region might disappear with the emergence profile of the prosthodontic components. The described

Multifunctional nanoparticles as a tissue adhesive and an injectable marker for image-guided procedures

Science.gov (United States)

Shin, Kwangsoo; Choi, Jin Woo; Ko, Giho; Baik, Seungmin; Kim, Dokyoon; Park, Ok Kyu; Lee, Kyoungbun; Cho, Hye Rim; Han, Sang Ihn; Lee, Soo Hong; Lee, Dong Jun; Lee, Nohyun; Kim, Hyo-Cheol; Hyeon, Taeghwan

2017-07-01

Tissue adhesives have emerged as an alternative to sutures and staples for wound closure and reconnection of injured tissues after surgery or trauma. Owing to their convenience and effectiveness, these adhesives have received growing attention particularly in minimally invasive procedures. For safe and accurate applications, tissue adhesives should be detectable via clinical imaging modalities and be highly biocompatible for intracorporeal procedures. However, few adhesives meet all these requirements. Herein, we show that biocompatible tantalum oxide/silica core/shell nanoparticles (TSNs) exhibit not only high contrast effects for real-time imaging but also strong adhesive properties. Furthermore, the biocompatible TSNs cause much less cellular toxicity and less inflammation than a clinically used, imageable tissue adhesive (that is, a mixture of cyanoacrylate and Lipiodol). Because of their multifunctional imaging and adhesive property, the TSNs are successfully applied as a hemostatic adhesive for minimally invasive procedures and as an immobilized marker for image-guided procedures.

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

DEFF Research Database (Denmark)

Hoadley, Katherine A; Yau, Christina; Wolf, Denise M

2014-01-01

Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform...... on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset...

Automated Analysis and Classification of Histological Tissue Features by Multi-Dimensional Microscopic Molecular Profiling.

Directory of Open Access Journals (Sweden)

Daniel P Riordan

Full Text Available Characterization of the molecular attributes and spatial arrangements of cells and features within complex human tissues provides a critical basis for understanding processes involved in development and disease. Moreover, the ability to automate steps in the analysis and interpretation of histological images that currently require manual inspection by pathologists could revolutionize medical diagnostics. Toward this end, we developed a new imaging approach called multidimensional microscopic molecular profiling (MMMP that can measure several independent molecular properties in situ at subcellular resolution for the same tissue specimen. MMMP involves repeated cycles of antibody or histochemical staining, imaging, and signal removal, which ultimately can generate information analogous to a multidimensional flow cytometry analysis on intact tissue sections. We performed a MMMP analysis on a tissue microarray containing a diverse set of 102 human tissues using a panel of 15 informative antibody and 5 histochemical stains plus DAPI. Large-scale unsupervised analysis of MMMP data, and visualization of the resulting classifications, identified molecular profiles that were associated with functional tissue features. We then directly annotated H&E images from this MMMP series such that canonical histological features of interest (e.g. blood vessels, epithelium, red blood cells were individually labeled. By integrating image annotation data, we identified molecular signatures that were associated with specific histological annotations and we developed statistical models for automatically classifying these features. The classification accuracy for automated histology labeling was objectively evaluated using a cross-validation strategy, and significant accuracy (with a median per-pixel rate of 77% per feature from 15 annotated samples for de novo feature prediction was obtained. These results suggest that high-dimensional profiling may advance the

Systematic bias in genomic classification due to contaminating non-neoplastic tissue in breast tumor samples.

Science.gov (United States)

Elloumi, Fathi; Hu, Zhiyuan; Li, Yan; Parker, Joel S; Gulley, Margaret L; Amos, Keith D; Troester, Melissa A

2011-06-30

Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.

Classification of cardiovascular tissues using LBP based descriptors and a cascade SVM.

Science.gov (United States)

Mazo, Claudia; Alegre, Enrique; Trujillo, Maria

2017-08-01

Histological images have characteristics, such as texture, shape, colour and spatial structure, that permit the differentiation of each fundamental tissue and organ. Texture is one of the most discriminative features. The automatic classification of tissues and organs based on histology images is an open problem, due to the lack of automatic solutions when treating tissues without pathologies. In this paper, we demonstrate that it is possible to automatically classify cardiovascular tissues using texture information and Support Vector Machines (SVM). Additionally, we realised that it is feasible to recognise several cardiovascular organs following the same process. The texture of histological images was described using Local Binary Patterns (LBP), LBP Rotation Invariant (LBPri), Haralick features and different concatenations between them, representing in this way its content. Using a SVM with linear kernel, we selected the more appropriate descriptor that, for this problem, was a concatenation of LBP and LBPri. Due to the small number of the images available, we could not follow an approach based on deep learning, but we selected the classifier who yielded the higher performance by comparing SVM with Random Forest and Linear Discriminant Analysis. Once SVM was selected as the classifier with a higher area under the curve that represents both higher recall and precision, we tuned it evaluating different kernels, finding that a linear SVM allowed us to accurately separate four classes of tissues: (i) cardiac muscle of the heart, (ii) smooth muscle of the muscular artery, (iii) loose connective tissue, and (iv) smooth muscle of the large vein and the elastic artery. The experimental validation was conducted using 3000 blocks of 100 × 100 sized pixels, with 600 blocks per class and the classification was assessed using a 10-fold cross-validation. using LBP as the descriptor, concatenated with LBPri and a SVM with linear kernel, the main four classes of tissues were

Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images

International Nuclear Information System (INIS)

Sahiner, B.; Chan, H.P.; Petrick, N.; Helvie, M.A.; Adler, D.D.; Goodsitt, M.M.; Wei, D.

1996-01-01

The authors investigated the classification of regions of interest (ROI's) on mammograms as either mass or normal tissue using a convolution neural network (CNN). A CNN is a back-propagation neural network with two-dimensional (2-D) weight kernels that operate on images. A generalized, fast and stable implementation of the CNN was developed. The input images to the CNN were obtained form the ROI's using two techniques. The first technique employed averaging and subsampling. The second technique employed texture feature extraction methods applied to small subregions inside the ROI. Features computed over different subregions were arranged as texture images, which were subsequently used as CNN inputs. The effects of CNN architecture and texture feature parameters on classification accuracy were studied. Receiver operating characteristic (ROC) methodology was used to evaluate the classification accuracy. A data set consisting of 168 ROI's containing biopsy-proven masses and 504 ROI's containing normal breast tissue was extracted from 168 mammograms by radiologists experienced in mammography. This data set was used for training and testing the CNN. With the best combination of CNN architecture and texture feature parameters, the area under the test ROC curve reached 0.87, which corresponded to a true-positive fraction of 90% at a false positive fraction of 31%. The results demonstrate the feasibility of using a CNN for classification of masses and normal tissue on mammograms

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.

Science.gov (United States)

Boskamp, Tobias; Lachmund, Delf; Oetjen, Janina; Cordero Hernandez, Yovany; Trede, Dennis; Maass, Peter; Casadonte, Rita; Kriegsmann, Jörg; Warth, Arne; Dienemann, Hendrik; Weichert, Wilko; Kriegsmann, Mark

2017-07-01

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

Polarimetry based partial least square classification of ex vivo healthy and basal cell carcinoma human skin tissues.

Science.gov (United States)

Ahmad, Iftikhar; Ahmad, Manzoor; Khan, Karim; Ikram, Masroor

2016-06-01

Optical polarimetry was employed for assessment of ex vivo healthy and basal cell carcinoma (BCC) tissue samples from human skin. Polarimetric analyses revealed that depolarization and retardance for healthy tissue group were significantly higher (ppolarimetry together with PLS statistics hold promise for automated pathology classification. Copyright © 2016 Elsevier B.V. All rights reserved.

Effects on MR images compression in tissue classification quality

International Nuclear Information System (INIS)

Santalla, H; Meschino, G; Ballarin, V

2007-01-01

It is known that image compression is required to optimize the storage in memory. Moreover, transmission speed can be significantly improved. Lossless compression is used without controversy in medicine, though benefits are limited. If we compress images lossy, where image can not be totally recovered; we can only recover an approximation. In this point definition of 'quality' is essential. What we understand for 'quality'? How can we evaluate a compressed image? Quality in images is an attribute whit several definitions and interpretations, which actually depend on the posterior use we want to give them. This work proposes a quantitative analysis of quality for lossy compressed Magnetic Resonance (MR) images, and their influence in automatic tissue classification, accomplished with these images

Contributions for classification of platelet rich plasma - proposal of a new classification: MARSPILL.

Science.gov (United States)

Lana, Jose Fabio Santos Duarte; Purita, Joseph; Paulus, Christian; Huber, Stephany Cares; Rodrigues, Bruno Lima; Rodrigues, Ana Amélia; Santana, Maria Helena; Madureira, João Lopo; Malheiros Luzo, Ângela Cristina; Belangero, William Dias; Annichino-Bizzacchi, Joyce Maria

2017-07-01

Platelet-rich plasma (PRP) has emerged as a significant therapy used in medical conditions with heterogeneous results. There are some important classifications to try to standardize the PRP procedure. The aim of this report is to describe PRP contents studying celular and molecular components, and also propose a new classification for PRP. The main focus is on mononuclear cells, which comprise progenitor cells and monocytes. In addition, there are important variables related to PRP application incorporated in this study, which are the harvest method, activation, red blood cells, number of spins, image guidance, leukocytes number and light activation. The other focus is the discussion about progenitor cells presence on peripherial blood which are interesting due to neovasculogenesis and proliferation. The function of monocytes (in tissue-macrophages) are discussed here and also its plasticity, a potential property for regenerative medicine treatments.

A new classification system for congenital laryngeal cysts.

Science.gov (United States)

Forte, Vito; Fuoco, Gabriel; James, Adrian

2004-06-01

A new classification system for congenital laryngeal cysts based on the extent of the cyst and on the embryologic tissue of origin is proposed. Retrospective chart review. The charts of 20 patients with either congenital or acquired laryngeal cysts that were treated surgically between 1987 and 2002 at the Hospital for Sick Children, Toronto were retrospectively reviewed. Clinical presentation, radiologic findings, surgical management, histopathology, and outcome were recorded. A new classification system is proposed to better appreciate the origin of these cysts and to guide in their successful surgical management. Fourteen of the supraglottic and subglottic simple mucous retention cysts posed no diagnostic or therapeutic challenge and were treated successfully by a single endoscopic excision or marsupialization. The remaining six patients with congenital cysts in the study were deemed more complex, and all required open surgical procedures for cure. On the basis of the analysis of the data of these patients, a new classification of congenital laryngeal cysts is proposed. Type I cysts are confined to the larynx, the cyst wall composed of endodermal elements only, and can be managed endoscopically. Type II cysts extend beyond the confines of the larynx and require an external approach. The Type II cysts are further subclassified histologically on the basis of the embryologic tissue of origin: IIa, composed of endoderm only and IIb, containing endodermal and mesodermal elements (epithelium and cartilage) in the wall of the cyst. A new classification system for congenital laryngeal cysts is proposed on the basis of the extent of the cyst and the embryologic tissue of origin. This classification can help guide the surgeon with initial management and help us better understand the origin of these cysts.

Classification of coronary artery tissues using optical coherence tomography imaging in Kawasaki disease

Science.gov (United States)

Abdolmanafi, Atefeh; Prasad, Arpan Suravi; Duong, Luc; Dahdah, Nagib

2016-03-01

Intravascular imaging modalities, such as Optical Coherence Tomography (OCT) allow nowadays improving diagnosis, treatment, follow-up, and even prevention of coronary artery disease in the adult. OCT has been recently used in children following Kawasaki disease (KD), the most prevalent acquired coronary artery disease during childhood with devastating complications. The assessment of coronary artery layers with OCT and early detection of coronary sequelae secondary to KD is a promising tool for preventing myocardial infarction in this population. More importantly, OCT is promising for tissue quantification of the inner vessel wall, including neo intima luminal myofibroblast proliferation, calcification, and fibrous scar deposits. The goal of this study is to classify the coronary artery layers of OCT imaging obtained from a series of KD patients. Our approach is focused on developing a robust Random Forest classifier built on the idea of randomly selecting a subset of features at each node and based on second- and higher-order statistical texture analysis which estimates the gray-level spatial distribution of images by specifying the local features of each pixel and extracting the statistics from their distribution. The average classification accuracy for intima and media are 76.36% and 73.72% respectively. Random forest classifier with texture analysis promises for classification of coronary artery tissue.

Is the stripping technique a tissue-sparing procedure in large simple ovarian cysts in children?

Science.gov (United States)

Arena, Francesco; Romeo, Carmelo; Castagnetti, Marco; Scalfari, GianFranco; Cimador, Marcello; Impellizzeri, Pietro; Villari, Daniela; Zimbaro, Fabrizio; DeGrazia, Enrico

2008-07-01

Stripping of the cystic wall is performed by gynecologists to treat large ovarian cysts. Information in the pediatric population is poor. We prospectively evaluated the pathologic specimens of large ovarian cyst to determine whether the stripping technique is a tissue-sparing procedure even in this age. We evaluated 5 patients. Samples were taken from the intermediate part of the cystic wall and from the layer covering the cyst during excision. The presence of ovarian tissue adjacent to the cyst wall, and the morphological features of the surrounding tissue were both evaluated. Pelvic ultrasound follow-up was also performed. Patients' mean age was 4.5 years (7 days to 12 years). All cysts were removed because all were symptomatic. The mean diameter was 86.6 mm (74-100 mm). Cysts were follicular in 2 cases, serous in other two, and endometriotic in 1 case. Adjacent ovarian tissue was present in 1 of 5 specimens and was approximately 1 to 2 mm in thickness. The layer adjacent to the cystic wall always appeared as normal ovarian tissue. Ultrasound scans at follow-up revealed presence of ovarian tissue. The stripping procedure for large ovarian cyst excision allows to spare the adjacent normal ovarian tissue even in pediatric age because ovarian tissue is rarely excised with the cyst wall during the procedure.

Improved classification and visualization of healthy and pathological hard dental tissues by modeling specular reflections in NIR hyperspectral images

Science.gov (United States)

Usenik, Peter; Bürmen, Miran; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan

2012-03-01

Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots, which are difficult to diagnose. Near-infrared (NIR) hyperspectral imaging is a new promising technique for early detection of demineralization which can classify healthy and pathological dental tissues. However, due to non-ideal illumination of the tooth surface the hyperspectral images can exhibit specular reflections, in particular around the edges and the ridges of the teeth. These reflections significantly affect the performance of automated classification and visualization methods. Cross polarized imaging setup can effectively remove the specular reflections, however is due to the complexity and other imaging setup limitations not always possible. In this paper, we propose an alternative approach based on modeling the specular reflections of hard dental tissues, which significantly improves the classification accuracy in the presence of specular reflections. The method was evaluated on five extracted human teeth with corresponding gold standard for 6 different healthy and pathological hard dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized regions. Principal component analysis (PCA) was used for multivariate local modeling of healthy and pathological dental tissues. The classification was performed by employing multiple discriminant analysis. Based on the obtained results we believe the proposed method can be considered as an effective alternative to the complex cross polarized imaging setups.

Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

Science.gov (United States)

Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

1990-01-01

Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

Science.gov (United States)

Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

2016-03-01

The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care

The use of Compton scattering to differentiate between classifications of normal and diseased breast tissue

Energy Technology Data Exchange (ETDEWEB)

Ryan, Elaine A; Farquharson, Michael J; Flinton, David M [School of Allied Health Sciences, City University, Charterhouse Square, London EC1M 6PA (United Kingdom)

2005-07-21

This study describes a technique for measuring the electron density of breast tissue utilizing Compton scattered photons. The K{sub {alpha}}{sub 2} line from a tungsten target industrial x-ray tube (57.97 keV) was used and the scattered x-rays collected at an angle of 30{sup 0}. At this angle the Compton and coherent photon peaks can be resolved using an energy dispersive detector and a peak fitting algorithm. The system was calibrated using solutions of known electron density. The results obtained from a pilot study of 22 tissues are presented. The tissue samples investigated comprise four different tissue classifications: adipose, malignancy, fibroadenoma and fibrocystic change (FCC). It is shown that there is a difference between adipose and malignant tissue, to a value of 9.0%, and between adipose and FCC, to a value of 12.7%. These figures are found to be significant by statistical analysis. The differences between adipose and fibroadenoma tissues (2.2%) and between malignancy and FCC (3.4%) are not significant. It is hypothesized that the alteration in glucose uptake within malignant cells may cause these tissues to have an elevated electron density. The fibrotic nature of tissue that has undergone FCC gives the highest measure of all tissue types.

The use of Compton scattering to differentiate between classifications of normal and diseased breast tissue

Science.gov (United States)

Ryan, Elaine A.; Farquharson, Michael J.; Flinton, David M.

2005-07-01

This study describes a technique for measuring the electron density of breast tissue utilizing Compton scattered photons. The Kα2 line from a tungsten target industrial x-ray tube (57.97 keV) was used and the scattered x-rays collected at an angle of 30°. At this angle the Compton and coherent photon peaks can be resolved using an energy dispersive detector and a peak fitting algorithm. The system was calibrated using solutions of known electron density. The results obtained from a pilot study of 22 tissues are presented. The tissue samples investigated comprise four different tissue classifications: adipose, malignancy, fibroadenoma and fibrocystic change (FCC). It is shown that there is a difference between adipose and malignant tissue, to a value of 9.0%, and between adipose and FCC, to a value of 12.7%. These figures are found to be significant by statistical analysis. The differences between adipose and fibroadenoma tissues (2.2%) and between malignancy and FCC (3.4%) are not significant. It is hypothesized that the alteration in glucose uptake within malignant cells may cause these tissues to have an elevated electron density. The fibrotic nature of tissue that has undergone FCC gives the highest measure of all tissue types.

The use of Compton scattering to differentiate between classifications of normal and diseased breast tissue

International Nuclear Information System (INIS)

Ryan, Elaine A; Farquharson, Michael J; Flinton, David M

2005-01-01

This study describes a technique for measuring the electron density of breast tissue utilizing Compton scattered photons. The K α2 line from a tungsten target industrial x-ray tube (57.97 keV) was used and the scattered x-rays collected at an angle of 30 0 . At this angle the Compton and coherent photon peaks can be resolved using an energy dispersive detector and a peak fitting algorithm. The system was calibrated using solutions of known electron density. The results obtained from a pilot study of 22 tissues are presented. The tissue samples investigated comprise four different tissue classifications: adipose, malignancy, fibroadenoma and fibrocystic change (FCC). It is shown that there is a difference between adipose and malignant tissue, to a value of 9.0%, and between adipose and FCC, to a value of 12.7%. These figures are found to be significant by statistical analysis. The differences between adipose and fibroadenoma tissues (2.2%) and between malignancy and FCC (3.4%) are not significant. It is hypothesized that the alteration in glucose uptake within malignant cells may cause these tissues to have an elevated electron density. The fibrotic nature of tissue that has undergone FCC gives the highest measure of all tissue types

Procedure of trace element analysis in oyster tissues by using X-ray fluorescence

International Nuclear Information System (INIS)

Vo Thi Tuong Hanh; Dinh Thi Bich Lieu; Dinh Thien Lam and Nguyen Manh Hung

2004-01-01

The procedure of trace element analysis such as Ca, Mn, Fe, Zn, Cu, Pb in molluscs (oyster tissues) was established by using X-ray fluorescence techniques. The procedure was investigated from the sample collection, drying, ashing ratio to the analytical techniques by using Cd-109, detector Si (Li) and the peak processing MCAPLUS program was applied for this study. The procedure is based on direct comparison with certified concentrations of international standard reference SRM 1566b Oyster Tissue of National Institute of Standards and Technology, Department of commerce, United States of America for Ca, Mn, Fe, Zn, Cu and the Standard Addition Methods for Pb. The accuracy of the Standard Addition Methods was estimated by CRM281 Rye Grass of Community Bureau of Reference-BCR, European Commission. The results of 10 samples which were collected from several markets in Hanoi are shown. (author)

Spiral wave classification using normalized compression distance: Towards atrial tissue spatiotemporal electrophysiological behavior characterization.

Science.gov (United States)

Alagoz, Celal; Guez, Allon; Cohen, Andrew; Bullinga, John R

2015-08-01

Analysis of electrical activation patterns such as re-entries during atrial fibrillation (Afib) is crucial in understanding arrhythmic mechanisms and assessment of diagnostic measures. Spiral waves are a phenomena that provide intuitive basis for re-entries occurring in cardiac tissue. Distinct spiral wave behaviors such as stable spiral waves, meandering spiral waves, and spiral wave break-up may have distinct electrogram manifestations on a mapping catheter. Hence, it is desirable to have an automated classification of spiral wave behavior based on catheter recordings for a qualitative characterization of spatiotemporal electrophysiological activity on atrial tissue. In this study, we propose a method for classification of spatiotemporal characteristics of simulated atrial activation patterns in terms of distinct spiral wave behaviors during Afib using two different techniques: normalized compressed distance (NCD) and normalized FFT (NFFTD). We use a phenomenological model for cardiac electrical propagation to produce various simulated spiral wave behaviors on a 2D grid and labeled them as stable, meandering, or breakup. By mimicking commonly used catheter types, a star shaped and a circular shaped both of which do the local readings from atrial wall, monopolar and bipolar intracardiac electrograms are simulated. Virtual catheters are positioned at different locations on the grid. The classification performance for different catheter locations, types and for monopolar or bipolar readings were also compared. We observed that the performance for each case differed slightly. However, we found that NCD performance is superior to NFFTD. Through the simulation study, we showed the theoretical validation of the proposed method. Our findings suggest that a qualitative wavefront activation pattern can be assessed during Afib without the need for highly invasive mapping techniques such as multisite simultaneous electrogram recordings.

Tissue classification and diagnostics using a fiber probe for combined Raman and fluorescence spectroscopy

Science.gov (United States)

Cicchi, Riccardo; Anand, Suresh; Crisci, Alfonso; Giordano, Flavio; Rossari, Susanna; De Giorgi, Vincenzo; Maio, Vincenza; Massi, Daniela; Nesi, Gabriella; Buccoliero, Anna Maria; Guerrini, Renzo; Pimpinelli, Nicola; Pavone, Francesco S.

2015-07-01

Two different optical fiber probes for combined Raman and fluorescence spectroscopic measurements were designed, developed and used for tissue diagnostics. Two visible laser diodes were used for fluorescence spectroscopy, whereas a laser diode emitting in the NIR was used for Raman spectroscopy. The two probes were based on fiber bundles with a central multimode optical fiber, used for delivering light to the tissue, and 24 surrounding optical fibers for signal collection. Both fluorescence and Raman spectra were acquired using the same detection unit, based on a cooled CCD camera, connected to a spectrograph. The two probes were successfully employed for diagnostic purposes on various tissues in a good agreement with common routine histology. This study included skin, brain and bladder tissues and in particular the classification of: malignant melanoma against melanocytic lesions and healthy skin; urothelial carcinoma against healthy bladder mucosa; brain tumor against dysplastic brain tissue. The diagnostic capabilities were determined using a cross-validation method with a leave-one-out approach, finding very high sensitivity and specificity for all the examined tissues. The obtained results demonstrated that the multimodal approach is crucial for improving diagnostic capabilities. The system presented here can improve diagnostic capabilities on a broad range of tissues and has the potential of being used for endoscopic inspections in the near future.

Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

Science.gov (United States)

Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

2014-01-01

We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

Soft Tissue Surgical Procedures for Optimizing Anterior Implant Esthetics

Science.gov (United States)

Ioannou, Andreas L.; Kotsakis, Georgios A.; McHale, Michelle G.; Lareau, Donald E.; Hinrichs, James E.; Romanos, Georgios E.

2015-01-01

Implant dentistry has been established as a predictable treatment with excellent clinical success to replace missing or nonrestorable teeth. A successful esthetic implant reconstruction is predicated on two fundamental components: the reproduction of the natural tooth characteristics on the implant crown and the establishment of soft tissue housing that will simulate a healthy periodontium. In order for an implant to optimally rehabilitate esthetics, the peri-implant soft tissues must be preserved and/or augmented by means of periodontal surgical procedures. Clinicians who practice implant dentistry should strive to achieve an esthetically successful outcome beyond just osseointegration. Knowledge of a variety of available techniques and proper treatment planning enables the clinician to meet the ever-increasing esthetic demands as requested by patients. The purpose of this paper is to enhance the implant surgeon's rationale and techniques beyond that of simply placing a functional restoration in an edentulous site to a level whereby an implant-supported restoration is placed in reconstructed soft tissue, so the site is indiscernible from a natural tooth. PMID:26124837

Vitrification of human ovarian tissue: effect of different solutions and procedures.

Science.gov (United States)

Amorim, Christiani Andrade; David, Anu; Van Langendonckt, Anne; Dolmans, Marie-Madeleine; Donnez, Jacques

2011-03-01

To test the effect of different vitrification solutions and procedures on the morphology of human preantral follicles. Pilot study. Gynecology research unit in a university hospital. Ovarian biopsies were obtained from nine women aged 22-35 years. Ovarian tissue fragments were subjected to [1] different vitrification solutions to test their toxicity or [2] different vitrification methods using plastic straws, medium droplets, or solid-surface vitrification before in vitro culture. Number of morphologically normal follicles after toxicity testing or vitrification with the different treatments determined by histologic analysis. In the toxicity tests, only VS3 showed similar results to fresh tissue before and after in vitro culture (fresh controls 1 and 2). In addition, this was the only solution able to completely vitrify. In all vitrification procedures, the percentage of normal follicles was lower than in controls. However, of the three protocols, the droplet method yielded a significantly higher proportion of normal follicles. Our experiments showed VS3 to have no deleterious effect on follicular morphology and to be able to completely vitrify, although vitrification procedures were found to affect human follicles. Nevertheless, the droplet method resulted in a higher percentage of morphologically normal follicles. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Procedure for the classification of professional accidents of members of the personnel – REMINDER

CERN Multimedia

HR Department

2011-01-01

HR Department would like to remind members of the personnel that, according to the procedure for an accident deemed to be occupational and according to paragraph 29 of Administrative Circular No. 14 (Rev.2), they are requested to complete an accident declaration form (HS 50) within ten working days after the accident has occurred*). Once this deadline has passed, HR Department will be unable to proceed with the classification of the accident and, consequently, medical expenses that may arise linked to this accident will be reimbursed under the non-occupational scheme. In addition, any request for the classification of occupational accidents must be accompanied by a medical certificate detailing the bodily injuries resulting from the accident in question.   _______________ *) Or within three months of its occurrence if the victim or his beneficiaries are materially unable to meet this deadline.

Dermal and inhalation acute toxic class methods: test procedures and biometric evaluations for the Globally Harmonized Classification System.

Science.gov (United States)

Holzhütter, H G; Genschow, E; Diener, W; Schlede, E

2003-05-01

The acute toxic class (ATC) methods were developed for determining LD(50)/LC(50) estimates of chemical substances with significantly fewer animals than needed when applying conventional LD(50)/LC(50) tests. The ATC methods are sequential stepwise procedures with fixed starting doses/concentrations and a maximum of six animals used per dose/concentration. The numbers of dead/moribund animals determine whether further testing is necessary or whether the test is terminated. In recent years we have developed classification procedures for the oral, dermal and inhalation routes of administration by using biometric methods. The biometric approach assumes a probit model for the mortality probability of a single animal and assigns the chemical to that toxicity class for which the best concordance is achieved between the statistically expected and the observed numbers of dead/moribund animals at the various steps of the test procedure. In previous publications we have demonstrated the validity of the biometric ATC methods on the basis of data obtained for the oral ATC method in two-animal ring studies with 15 participants from six countries. Although the test procedures and biometric evaluations for the dermal and inhalation ATC methods have already been published, there was a need for an adaptation of the classification schemes to the starting doses/concentrations of the Globally Harmonized Classification System (GHS) recently adopted by the Organization for Economic Co-operation and Development (OECD). Here we present the biometric evaluation of the dermal and inhalation ATC methods for the starting doses/concentrations of the GHS and of some other international classification systems still in use. We have developed new test procedures and decision rules for the dermal and inhalation ATC methods, which require significantly fewer animals to provide predictions of toxicity classes, that are equally good or even better than those achieved by using the conventional LD(50)/LC

[Biocybernetic approach to the thermometric methods of blood supply measurements of periodontal tissues].

Science.gov (United States)

Pastusiak, J; Zakrzewski, J

1988-11-01

Specific biocybernetic approach to the problem of the blood supply determination of paradontium tissues by means of thermometric methods has been presented in the paper. The compartment models of the measuring procedure have been given. Dilutodynamic methology and classification has been applied. Such an approach enables to select appropriate biophysical parameters describing the state of blood supply of paradontium tissues and optimal design of transducers and measuring methods.

Comparing the 810nm diode laser with conventional surgery in orthodontic soft tissue procedures.

Science.gov (United States)

Ize-Iyamu, I N; Saheeb, B D; Edetanlen, B E

2013-09-01

To compare the use of the 810nm diode laser with conventional surgery in the management of soft tissue mucogingival problems associated with orthodontic treatment. Orthodontic patients requiring different soft tissue surgical procedures were randomly assigned to receive conventional surgery or soft tissue diode laser, (wavelength 810 nm). Parameters documented include the type of anaesthesia used, intra and post operative pain, bleeding, the use of scalpel and sutures. The chi-squared test was used to test for significance at 95% confidence level. Probability values (p-values) less than 0.05 were regarded as significant. Only 2(16.7%) of the procedures carried out with the soft tissue laser required infiltration anaesthesia compared to 10 (90.9%) with conventional surgery and this was significant (Pdiode laser (Pdiode laser. No sutures were used in all soft tissue cases managed with the diode laser and this was significant (Plaser compared with conventional surgery. Orthodontic patients treated with the diode laser required less infiltration anaesthesia, had reduced bleeding during and after surgery, rapid postoperative haemostasis, elimination of the need for sutures and an improved postoperative comfort and healing.

Sample preparation procedure for PIXE elemental analysis on soft tissues

International Nuclear Information System (INIS)

Kubica, B.; Kwiatek, W.M.; Dutkiewicz, E.M.; Lekka, M.

1997-01-01

Trace element analysis is one of the most important field in analytical chemistry. There are several instrumental techniques which are applied for determinations of microscopic elemental content. The PIXE (Proton Induced X-ray Emission) technique is one of the nuclear techniques that is commonly applied for such purpose due to its multielemental analysis possibilities. The aim of this study was to establish the optimal conditions for target preparation procedure. In this paper two different approaches to the topic are presented and widely discussed. The first approach was the traditional pellet technique and the second one was mineralization procedure. For the analysis soft tissue such as liver was used. Some results are also presented on water samples. (author)

Analytical procedures for bulk frozen-hydrated biological tissues

International Nuclear Information System (INIS)

Echlin, P.; Hayes, T.L.; McKoon, M.

1983-01-01

The main advantage of using solid frozen samples for elemental x-ray microanalysis is the ease with which they may be prepared and maintained in the frozen-hydrated state. Within the limits imposed by the reduced spatial resolution of the method, the morphological identification of the tissue components is comparatively easy. Bearing in mind these limitations, the authors have carried out an analysis for several elements in the developing root tips of Lemna minor L (Duckweed). Fresh root tips of Lemna minor L, briefly encapsulated in a polymeric cryoprotectant, are quench frozen in melting nitrogen at ca. 70 0 K and transferred to the pre-cooled cold stage of an AMray Biochamber. The analysis was carried out by means of a Kevex energy-dispersive detector by use of the peak-to-background ratio method. These procedures allow the authors to obtain flat fracture faces in which they have been able to measure the relative concentrations of various elements at the various stages of differentiation in the root tissue

Data-driven classification of ventilated lung tissues using electrical impedance tomography

International Nuclear Information System (INIS)

Gómez-Laberge, Camille; Hogan, Matthew J; Elke, Gunnar; Weiler, Norbert; Frerichs, Inéz; Adler, Andy

2011-01-01

Current methods for identifying ventilated lung regions utilizing electrical impedance tomography images rely on dividing the image into arbitrary regions of interest (ROI), manually delineating ROI, or forming ROI with pixels whose signal properties surpass an arbitrary threshold. In this paper, we propose a novel application of a data-driven classification method to identify ventilated lung ROI based on forming k clusters from pixels with correlated signals. A standard first-order model for lung mechanics is then applied to determine which ROI correspond to ventilated lung tissue. We applied the method in an experimental study of 16 mechanically ventilated swine in the supine position, which underwent changes in positive end-expiratory pressure (PEEP) and fraction of inspired oxygen (F I O 2 ). In each stage of the experimental protocol, the method performed best with k = 4 and consistently identified 3 lung tissue ROI and 1 boundary tissue ROI in 15 of the 16 subjects. When testing for changes from baseline in lung position, tidal volume, and respiratory system compliance, we found that PEEP displaced the ventilated lung region dorsally by 2 cm, decreased tidal volume by 1.3%, and increased the respiratory system compliance time constant by 0.3 s. F I O 2 decreased tidal volume by 0.7%. All effects were tested at p < 0.05 with n = 16. These findings suggest that the proposed ROI detection method is robust and sensitive to ventilation dynamics in the experimental setting

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

International Nuclear Information System (INIS)

Oliveira, D L L; Batista, V R; Duarte, Y A S; Nascimento, M Z; Neves, L A; Godoy, M F; Jacomini, R S; Arruda, P F F; Neto, D S

2014-01-01

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis

Expected Classification Accuracy

Directory of Open Access Journals (Sweden)

Lawrence M. Rudner

2005-08-01

Full Text Available Every time we make a classification based on a test score, we should expect some number..of misclassifications. Some examinees whose true ability is within a score range will have..observed scores outside of that range. A procedure for providing a classification table of..true and expected scores is developed for polytomously scored items under item response..theory and applied to state assessment data. A simplified procedure for estimating the..table entries is also presented.

Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study

Science.gov (United States)

Kontos, Despina; Berger, Rachelle; Bakic, Predrag R.; Maidment, Andrew D. A.

2009-02-01

Mammographic breast density is a known breast cancer risk factor. Studies have shown the potential to automate breast density estimation by using computerized texture-based segmentation of the dense tissue in mammograms. Digital breast tomosynthesis (DBT) is a tomographic x-ray breast imaging modality that could allow volumetric breast density estimation. We evaluated the feasibility of distinguishing between dense and fatty breast regions in DBT using computer-extracted texture features. Our long-term hypothesis is that DBT texture analysis can be used to develop 3D dense tissue segmentation algorithms for estimating volumetric breast density. DBT images from 40 women were analyzed. The dense tissue area was delineated within each central source projection (CSP) image using a thresholding technique (Cumulus, Univ. Toronto). Two (2.5cm)2 ROIs were manually selected: one within the dense tissue region and another within the fatty region. Corresponding (2.5cm)3 ROIs were placed within the reconstructed DBT images. Texture features, previously used for mammographic dense tissue segmentation, were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance. Different texture features appeared to perform best in the 3D reconstructed DBT compared to the 2D CSP images. Fractal dimension was superior in DBT (AUC=0.90), while contrast was best in CSP images (AUC=0.92). We attribute these differences to the effects of tissue superimposition in CSP and the volumetric visualization of the breast tissue in DBT. Our results suggest that novel approaches, different than those conventionally used in projection mammography, need to be investigated in order to develop DBT dense tissue segmentation algorithms for estimating volumetric breast density.

Tissue classifications in Monte Carlo simulations of patient dose for photon beam tumor treatments

Science.gov (United States)

Lin, Mu-Han; Chao, Tsi-Chian; Lee, Chung-Chi; Tung-Chieh Chang, Joseph; Tung, Chuan-Jong

2010-07-01

The purpose of this work was to study the calculated dose uncertainties induced by the material classification that determined the interaction cross-sections and the water-to-material stopping-power ratios. Calculations were made for a head- and neck-cancer patient treated with five intensity-modulated radiotherapy fields using 6 MV photon beams. The patient's CT images were reconstructed into two voxelized patient phantoms based on different CT-to-material classification schemes. Comparisons of the depth-dose curve of the anterior-to-posterior field and the dose-volume-histogram of the treatment plan were used to evaluate the dose uncertainties from such schemes. The results indicated that any misassignment of tissue materials could lead to a substantial dose difference, which would affect the treatment outcome. To assure an appropriate material assignment, it is desirable to have different conversion tables for various parts of the body. The assignment of stopping-power ratio should be based on the chemical composition and the density of the material.

Tissue classifications in Monte Carlo simulations of patient dose for photon beam tumor treatments

International Nuclear Information System (INIS)

Lin, Mu-Han; Chao, Tsi-Chian; Lee, Chung-Chi; Tung-Chieh Chang, Joseph; Tung, Chuan-Jong

2010-01-01

The purpose of this work was to study the calculated dose uncertainties induced by the material classification that determined the interaction cross-sections and the water-to-material stopping-power ratios. Calculations were made for a head- and neck-cancer patient treated with five intensity-modulated radiotherapy fields using 6 MV photon beams. The patient's CT images were reconstructed into two voxelized patient phantoms based on different CT-to-material classification schemes. Comparisons of the depth-dose curve of the anterior-to-posterior field and the dose-volume-histogram of the treatment plan were used to evaluate the dose uncertainties from such schemes. The results indicated that any misassignment of tissue materials could lead to a substantial dose difference, which would affect the treatment outcome. To assure an appropriate material assignment, it is desirable to have different conversion tables for various parts of the body. The assignment of stopping-power ratio should be based on the chemical composition and the density of the material.

Multiplex coherent anti-Stokes Raman scattering microspectroscopy of brain tissue with higher ranking data classification for biomedical imaging

Science.gov (United States)

Pohling, Christoph; Bocklitz, Thomas; Duarte, Alex S.; Emmanuello, Cinzia; Ishikawa, Mariana S.; Dietzeck, Benjamin; Buckup, Tiago; Uckermann, Ortrud; Schackert, Gabriele; Kirsch, Matthias; Schmitt, Michael; Popp, Jürgen; Motzkus, Marcus

2017-06-01

Multiplex coherent anti-Stokes Raman scattering (MCARS) microscopy was carried out to map a solid tumor in mouse brain tissue. The border between normal and tumor tissue was visualized using support vector machines (SVM) as a higher ranking type of data classification. Training data were collected separately in both tissue types, and the image contrast is based on class affiliation of the single spectra. Color coding in the image generated by SVM is then related to pathological information instead of single spectral intensities or spectral differences within the data set. The results show good agreement with the H&E stained reference and spontaneous Raman microscopy, proving the validity of the MCARS approach in combination with SVM.

Energetic soft-tissue treatment technologies: an overview of procedural fundamentals and safety factors

NARCIS (Netherlands)

van de Berg, N. J.; van den Dobbelsteen, J. J.; Jansen, F. W.; Grimbergen, C. A.; Dankelman, J.

2013-01-01

Energy administered during soft-tissue treatments may cauterize, coagulate, seal, or otherwise affect underlying structures. A general overview of the functionality, procedural outcomes, and associated risks of these treatments, however, is not yet generally available. In addition, literature is

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

Science.gov (United States)

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

Science.gov (United States)

Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

2013-01-01

The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many

Automated classification of immunostaining patterns in breast tissue from the human protein Atlas

Directory of Open Access Journals (Sweden)

Issac Niwas Swamidoss

2013-01-01

Full Text Available Background: The Human Protein Atlas (HPA is an effort to map the location of all human proteins (http://www.proteinatlas.org/. It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. Materials and Methods: The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM features, complex wavelet co-occurrence matrix (CWCM features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM and linear discriminant analysis (LDA classifier. Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. Results: We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Conclusions: Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for

Synthetic aperture tissue and flow ultrasound imaging

DEFF Research Database (Denmark)

Nikolov, Svetoslav

imaging applied to medical ultrasound. It is divided into two major parts: tissue and blood flow imaging. Tissue imaging using synthetic aperture algorithms has been investigated for about two decades, but has not been implemented in medical scanners yet. Among the other reasons, the conventional scanning...... and beamformation methods are adequate for the imaging modalities in clinical use - the B-mode imaging of tissue structures, and the color mapping of blood flow. The acquisition time, however, is too long, and these methods fail to perform real-time three-dimensional scans. The synthetic transmit aperture......, on the other hand, can create a Bmode image with as little as 2 emissions, thus significantly speeding-up the scan procedure. The first part of the dissertation describes the synthetic aperture tissue imaging. It starts with an overview of the efforts previously made by other research groups. A classification...

Automatic breast tissue density estimation scheme in digital mammography images

Science.gov (United States)

Menechelli, Renan C.; Pacheco, Ana Luisa V.; Schiabel, Homero

2017-03-01

Cases of breast cancer have increased substantially each year. However, radiologists are subject to subjectivity and failures of interpretation which may affect the final diagnosis in this examination. The high density features in breast tissue are important factors related to these failures. Thus, among many functions some CADx (Computer-Aided Diagnosis) schemes are classifying breasts according to the predominant density. In order to aid in such a procedure, this work attempts to describe automated software for classification and statistical information on the percentage change in breast tissue density, through analysis of sub regions (ROIs) from the whole mammography image. Once the breast is segmented, the image is divided into regions from which texture features are extracted. Then an artificial neural network MLP was used to categorize ROIs. Experienced radiologists have previously determined the ROIs density classification, which was the reference to the software evaluation. From tests results its average accuracy was 88.7% in ROIs classification, and 83.25% in the classification of the whole breast density in the 4 BI-RADS density classes - taking into account a set of 400 images. Furthermore, when considering only a simplified two classes division (high and low densities) the classifier accuracy reached 93.5%, with AUC = 0.95.

Is overall similarity classification less effortful than single-dimension classification?

Science.gov (United States)

Wills, Andy J; Milton, Fraser; Longmore, Christopher A; Hester, Sarah; Robinson, Jo

2013-01-01

It is sometimes argued that the implementation of an overall similarity classification is less effortful than the implementation of a single-dimension classification. In the current article, we argue that the evidence securely in support of this view is limited, and report additional evidence in support of the opposite proposition--overall similarity classification is more effortful than single-dimension classification. Using a match-to-standards procedure, Experiments 1A, 1B and 2 demonstrate that concurrent load reduces the prevalence of overall similarity classification, and that this effect is robust to changes in the concurrent load task employed, the level of time pressure experienced, and the short-term memory requirements of the classification task. Experiment 3 demonstrates that participants who produced overall similarity classifications from the outset have larger working memory capacities than those who produced single-dimension classifications initially, and Experiment 4 demonstrates that instructions to respond meticulously increase the prevalence of overall similarity classification.

A Novel Texture Classification Procedure by using Association Rules

Directory of Open Access Journals (Sweden)

L. Jaba Sheela

2008-11-01

Full Text Available Texture can be defined as a local statistical pattern of texture primitives in observer’s domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules have been used in various applications during the past decades. Association rules capture both structural and statistical information, and automatically identify the structures that occur most frequently and relationships that have significant discriminative power. So, association rules can be adapted to capture frequently occurring local structures in textures. This paper describes the usage of association rules for texture classification problem. The performed experimental studies show the effectiveness of the association rules. The overall success rate is about 98%.

Immediate placement and provisionalization of maxillary anterior single implant with guided bone regeneration, connective tissue graft, and coronally positioned flap procedures.

Science.gov (United States)

Waki, Tomonori; Kan, Joseph Y K

2016-01-01

Immediate implant placement and provisionalization in the esthetic zone have been documented with success. The benefit of immediate implant placement and provisionalization is the preservation of papillary mucosa. However, in cases with osseous defects presenting on the facial bony plate, immediate implant placement procedures have resulted in facial gingival recession. Subepithelial connective tissue grafts for immediate implant placement and provisionalization procedures have been reported with a good esthetic outcome. Biotype conversion around implants with subepithelial connective tissue grafts have been advocated, and the resulting tissues appear to be more resistant to recession. The dimensions of peri-implant mucosa in a thick biotype were significantly greater than in a thin biotype. Connective tissue graft with coronally positioned flap procedures on natural teeth has also been documented with success. This article describes a technique combining immediate implant placement, provisionalization, guided bone regeneration (GBR), connective tissue graft, and a coronally positioned flap in order to achieve more stable peri-implant tissue in facial osseous defect situations.

Automatic classification of tissue malignancy for breast carcinoma diagnosis.

Science.gov (United States)

Fondón, Irene; Sarmiento, Auxiliadora; García, Ana Isabel; Silvestre, María; Eloy, Catarina; Polónia, António; Aguiar, Paulo

2018-05-01

Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images. We provide four malignancy levels as the output of the system: normal, benign, in situ and invasive. The method is based on the calculation of three sets of features related to nuclei, colour regions and textures considering local characteristics and global image properties. By taking advantage of well-established image processing techniques, we build a feature vector for each image that serves as an input to an SVM (Support Vector Machine) classifier with a quadratic kernel. The method has been rigorously evaluated, first with a 5-fold cross-validation within an initial set of 120 images, second with an external set of 30 different images and third with images with artefacts included. Accuracy levels range from 75.8% when the 5-fold cross-validation was performed to 75% with the external set of new images and 61.11% when the extremely difficult images were added to the classification experiment. The experimental results indicate that the proposed method is capable of distinguishing between four malignancy levels with high accuracy. Our results are close to those obtained with recent deep learning-based methods. Moreover, it performs better than other state-of-the-art methods based on feature extraction, and it can help improve the CAD of breast cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of digestion procedures used for the determination of boron in biological tissues by ICP-AES [inductively-coupled, plasma-atomic emission spectroscopy

International Nuclear Information System (INIS)

Bauer, W.F.; Miller, D.L.; Steele, S.M.

1988-01-01

A study was designed to identify the most accurate and reliable procedures for the digestion of biological tissues prior to the determination of boron by inductively-coupled, plasma-atomic emission spectroscopy (ICP-AES). The four procedures used in this study were an acid bomb digestion and digestions performed in test tubes using perchloric acid and hydrogen peroxide, nitric acid and hydrogen peroxide, and nitric acid alone. Digestions using nitric acid and hydrogen peroxide and nitric acid alone were performed in a manner analogous to the perchloric acid/hydrogen peroxide procedure. The tissues used in the study were from dogs that had been administered a boron compound (Na 2 B 12 H 11 SH) and included two brain tissues, a liver and a tongue. These tissues were selected in order to eliminate results that may be due to surface spiking only. None of the test tube procedures were successful in completely dissolving the samples, as was evidenced by residual color and a coagulated precipitate. The amount of precipitate was much larger for the brain tissues in all cases. The acid bomb digestion and the perchloric acid/hydrogen peroxide procedures gave comparable boron concentrations for all of the tissues in this study. 2 refs., 1 tab

Wagner classification and culture analysis of diabetic foot infection

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Fatma Bozkurt

2011-03-01

Full Text Available The aim of this study was to determine the concordance ratio between microorganisms isolated from deep tissue culture and those from superficial culture in patients with diabetic foot according to Wagner’s wound classification method.Materials and methods: A total of 63 patients with Diabetic foot infection, who were admitted to Dicle University Hospital between October 2006 and November 2007, were included into the study. Wagner’s classification method was used for wound classification. For microbiologic studies superficial and deep tissue specimens were obtained from each patient, and were rapidly sent to laboratory for aerob and anaerob cultures. Microbiologic data were analyzed and interpreted in line with sensitivity and specifity formula.Results: Thirty-eight (60% of the patients were in Wagner’s classification ≤2, while 25 (40% patients were Wagner’s classification ≥3. According to our culture results, 66 (69% Gr (+ and 30 (31% Gr (- microorganisms grew in Wagner classification ≤2 patients. While in Wagner classification ≥3; 25 (35% Gr (+ and 46 (65% Gr (- microorganisms grew. Microorganisms grew in 89% of superficial cultures and 64% of the deep tissue cultures in patients with Wagner classification ≤2, while microorganism grew in 64% of Wagner classification ≥3.Conclusion: In ulcers of diabetic food infections, initial treatment should be started according to result of sterile superficial culture, but deep tissue culture should be taken, if unresponsive to initial treatment.

Evaluation of different tissue de-paraffinization procedures for infrared spectral imaging.

Science.gov (United States)

Nallala, Jayakrupakar; Lloyd, Gavin Rhys; Stone, Nicholas

2015-04-07

In infrared spectral histopathology, paraffin embedded tissues are often de-paraffinized using chemical agents such as xylene and hexane. These chemicals are known to be toxic and the routine de-waxing procedure is time consuming. A comparative study was carried out to identify alternate de-paraffinization methods by using paraffin oil and electronic de-paraffinization (using a mathematical computer algorithm) and their effectiveness was compared to xylene and hexane. Sixteen adjacent tissue sections obtained from a single block of a normal colon tissue were de-paraffinized using xylene, hexane and paraffin oil (+ hexane wash) at five different time points each for comparison. One section was reserved unprocessed for electronic de-paraffinization based on a modified extended multiplicative signal correction (EMSC). IR imaging was carried out on these tissue sections. Coefficients based on the fit of a pure paraffin model to the IR images were then calculated to estimate the amount of paraffin remaining after processing. Results indicate that on average xylene removes more paraffin in comparison to hexane and paraffin oil although the differences were small. This makes paraffin oil, followed by a hexane wash, an interesting and less toxic alternative method of de-paraffinization. However, none of the chemical methods removed paraffin completely from the tissues at any given time point. Moreover, paraffin was removed more easily from the glandular regions than the connective tissue regions indicating a form of differential paraffin retention based on the histology. In such cases, the use of electronic de-paraffinization to neutralize such variances across different tissue regions might be considered. Moreover it is faster, reduces scatter artefacts by index matching and enables samples to be easily stored for further analysis if required.

Facial aging: A clinical classification

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Shiffman Melvin

2007-01-01

Full Text Available The purpose of this classification of facial aging is to have a simple clinical method to determine the severity of the aging process in the face. This allows a quick estimate as to the types of procedures that the patient would need to have the best results. Procedures that are presently used for facial rejuvenation include laser, chemical peels, suture lifts, fillers, modified facelift and full facelift. The physician is already using his best judgment to determine which procedure would be best for any particular patient. This classification may help to refine these decisions.

Automatic Genre Classification of Musical Signals

Science.gov (United States)

Barbedo, Jayme Garcia sArnal; Lopes, Amauri

2006-12-01

We present a strategy to perform automatic genre classification of musical signals. The technique divides the signals into 21.3 milliseconds frames, from which 4 features are extracted. The values of each feature are treated over 1-second analysis segments. Some statistical results of the features along each analysis segment are used to determine a vector of summary features that characterizes the respective segment. Next, a classification procedure uses those vectors to differentiate between genres. The classification procedure has two main characteristics: (1) a very wide and deep taxonomy, which allows a very meticulous comparison between different genres, and (2) a wide pairwise comparison of genres, which allows emphasizing the differences between each pair of genres. The procedure points out the genre that best fits the characteristics of each segment. The final classification of the signal is given by the genre that appears more times along all signal segments. The approach has shown very good accuracy even for the lowest layers of the hierarchical structure.

Optimization of wet digestion procedure of blood and tissue for selenium determination by means of 75Se tracer

International Nuclear Information System (INIS)

Holynska, B.; Lipinska, K.

1977-01-01

Selenium-75 tracer has been used for optimization of analytical procedure of selenium determination in blood and tissue. Wet digestion procedure and reduction of selenium to its elemental form with tellurium as coprecipitant have been tested. Recovery of selenium obtained with the use of optimized analytical procedure amounts up 95% and precision is equal to 4.2%. (author)

Classification of Laser Induced Fluorescence Spectra from Normal and Malignant bladder tissues using Learning Vector Quantization Neural Network in Bladder Cancer Diagnosis

DEFF Research Database (Denmark)

Karemore, Gopal Raghunath; Mascarenhas, Kim Komal; Patil, Choudhary

2008-01-01

In the present work we discuss the potential of recently developed classification algorithm, Learning Vector Quantization (LVQ), for the analysis of Laser Induced Fluorescence (LIF) Spectra, recorded from normal and malignant bladder tissue samples. The algorithm is prototype based and inherently...

[Long-term outcome of aortic valve sparing procedures in connective tissue disorders].

Science.gov (United States)

Tanaka, Hiroshi; Ogino, H; Matsuda, H; Minatoya, K; Sasaki, N

2009-10-01

The aim of this study is to determine the long-term outcome of aortic valve sparing procedures for patients having connective tissue disorder. Between 1993 and 2008, the aortic valve sparing surgery was performed in 94 patients having aortic root dilatation. Eighty patients of them (37.2 +/- 13.4 years, 50 male) had cystic medial necrosis in the aortic wall, which was confirmed the pathological examination. We reviewed these patients. Sixty percent (48/80) had Marfan syndrome, 5% (4/80) had Loeyz-Dietz syndrome, 2% (2/80) had bicuspid aortic valve, and 11% (9/80) had aortic dissection. Our reimplantation procedure has been refined as followed: with a tube graft in 41, a tube graft with creation of neo-sinuses in 11, and a Valsalva graft in 14. Fourteen patients underwent the remodeling procedure. The follow-up rate was 100% with the duration of 3.7+/- 3.4 years. There were no operative death but six late deaths. Seventeen (21.3%) patients required aortic valve replacement, for recurrent aortic insufficiency in 13 and infection in 4. Freedom from reoperation was 80%, 43%, and freedom from moderate or severe aortic insufficiency was 80%, 54%, at 5 and 10 years, respectively. Pathological findings of the aortic valve obtained in the reoperations showed elongation and prolapse of the aortic valve due to myxomatous degeneration and fibrous thickening caused by aortic insufficiency. Even in connective tissue disorders, aortic valve sparing operation is associated with acceptable long-term durability, although cusp degeneration resulting in recurrent aortic insufficiency might be progressive.

Tissue Banking: Current procedures, ethical consideration and ...

African Journals Online (AJOL)

Tissue banking provides safe and effective cells and tissues for transplantation in reconstruction surgery. Bone, amnion, skin, cartilage, heart valves and xenograft tissues are the most commonly used biological tissues. Acquisition of tissue is dependent on elaborate donor screening criteria based on medical and social ...

Three-dimensional analysis and classification of arteries in the skin and subcutaneous adipofascial tissue by computer graphics imaging.

Science.gov (United States)

Nakajima, H; Minabe, T; Imanishi, N

1998-09-01

To develop new types of surgical flaps that utilize portions of the skin and subcutaneous tissue (e.g., a thin flap or an adipofascial flap), three-dimensional investigation of the vasculature in the skin and subcutaneous tissue has been anticipated. In the present study, total-body arterial injection and three-dimensional imaging of the arteries by computer graphics were performed. The full-thickness skin and subcutaneous adipofascial tissue samples, which were obtained from fresh human cadavers injected with radio-opaque medium, were divided into three distinct layers. Angiograms of each layer were introduced into a personal computer to construct three-dimensional images. On a computer monitor, each artery was shown color-coded according to the three portions: the deep adipofascial layer, superficial adipofascial layer, and dermis. Three-dimensional computerized images of each artery in the skin and subcutaneous tissue revealed the components of each vascular plexus and permitted their classification into six types. The distribution of types in the body correlated with the tissue mobility of each area. Clinically, appreciation of the three-dimensional structure of the arteries allowed the development of several new kinds of flaps.

FIRST METATARSOPHALANGEAL JOINT OSTEOARTHRITIS: PERCUTANEOUS SURGERY, CHOICE OF A SURGICAL PROCEDURE, CLINICAL AND RADIOGRAPHIC CLASSIFICATION

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S. Yu. Berezhnoy

2017-01-01

Full Text Available Introduction. Hallux rigidus is observed in approximately 2.5% of the adult population. Until now neither a unified classification of hallux rigidus appears to exist nor any clear principles to choose the surgical method. The variety of clinical and radiological signs explains the difficulties in establishing a comprehensive classification system and in selection of the criteria for surgical procedure. There are few published reports about hallux rigidus percutaneous surgical treatment. Existing papers are dedicated to a limited number of percutaneous techniques.The purpose of this study was to evaluate the efficacy of percutaneous techniques for surgical treatment of the first metatarsophalangeal joint osteoarthritis; to specify factors determining the choice of procedure; to develop a grading system of the hallux rigidus severity which will help in selection of surgery. Materials and methods. Based on 156 surgeries (107 patients the author demonstrated the possibilities of percutaneous techniques in the surgical treatment of hallux rigidus of different stages as well as provided a brief description of used surgical techniques.Results. The mean age of patients was 48.8 years (ranged from 18 to 73. The mean follow-up was 7 months (ranged from 3 to 54. At the specified time the treatment outcomes of 103 patients (150 feet were analyzed. Mean hospital stay was 0.78 days (ranged from 0 to 1. No infectious or wound-healing problems were observed. Overall, the patients were completely satisfied with the outcomes of 89 surgical treatment, qualified satisfaction was reported with patients in respect of outcomes of 57 surgeries. Four unsatisfactory outcomes were observed. The role of the relatively long first metatarsal in the development of hallux rigidus was confirmed. Conclusion. Percutaneous techniques provide successful treatment for all stages of hallux rigidus. The choice of a specific surgical technique may be challenging and requires

[Distal soft-tissue procedure in hallux valgus deformity].

Science.gov (United States)

Arbab, D; Wingenfeld, C; Frank, D; Bouillon, B; König, D P

2016-04-01

Distal, lateral soft tissue release to restore mediolateral balance of the first metatarsophalangeal (MTP) joint in hallux valgus deformity. Incision of the adductor hallucis tendon from the fibular sesamoid, the lateral capsule, the lateral collateral ligament, and the lateral metatarsosesamoid ligament. Hallux valgus deformities or recurrent hallux valgus deformities with an incongruent MTP joint. General medical contraindications to surgical interventions. Painful stiffness of the MTP joint, osteonecrosis, congruent joint. Relative contraindications: connective tissue diseases (Marfan syndrome, Ehler-Danlos syndrome). Longitudinal, dorsal incision in the first intermetatarsal web space between the first and second MTP joint. Blunt dissection and identification of the adductor hallucis tendon. Release of the adductor tendon from the fibular sesamoid. Incision of the lateral capsule, the lateral collateral ligament, and the lateral metatarsosesamoid ligament. Postoperative management depends on bony correction. In joint-preserving procedures, dressing for 3 weeks in corrected position. Subsequently hallux valgus orthosis at night and a toe spreader for a further 3 months. Passive mobilization of the first MTP joint. Postoperative weight-bearing according to the osteotomy. A total of 31 patients with isolated hallux valgus deformity underwent surgery with a Chevron and Akin osteotomy and a distal medial and lateral soft tissue balancing. The mean preoperative intermetatarsal (IMA) angle was 12.3° (range 11-15°); the hallux valgus (HV) angle was 28.2° (25-36°). The mean follow-up was 16.4 months (range 12-22 months). The mean postoperative IMA correction ranged between 2 and 7° (mean 5.2°); the mean HV correction was 15.5° (range 9-21°). In all, 29 patients (93%) were satisfied or very satisfied with the postoperative outcome, while 2 patients (7%) were not satisfied due to one delayed wound healing and one recurrent hallux valgus deformity. There were no

Definition of pertinent parameters for the evaluation of articular cartilage repair tissue with high-resolution magnetic resonance imaging

International Nuclear Information System (INIS)

Marlovits, Stefan; Striessnig, Gabriele; Resinger, Christoph T.; Aldrian, Silke M.; Vecsei, Vilmos; Imhof, Herwig; Trattnig, Siegfried

2004-01-01

To evaluate articular cartilage repair tissue after biological cartilage repair, we propose a new technique of non-invasive, high-resolution magnetic resonance imaging (MRI) and define a new classification system. For the definition of pertinent variables the repair tissue of 45 patients treated with three different techniques for cartilage repair (microfracture, autologous osteochondral transplantation, and autologous chondrocyte transplantation) was analyzed 6 and 12 months after the procedure. High-resolution imaging was obtained with a surface phased array coil placed over the knee compartment of interest and adapted sequences were used on a 1 T MRI scanner. The analysis of the repair tissue included the definition and rating of nine pertinent variables: the degree of filling of the defect, the integration to the border zone, the description of the surface and structure, the signal intensity, the status of the subchondral lamina and subchondral bone, the appearance of adhesions and the presence of synovitis. High-resolution MRI, using a surface phased array coil and specific sequences, can be used on every standard 1 or 1.5 T MRI scanner according to the in-house standard protocols for knee imaging in patients who have had cartilage repair procedures without substantially prolonging the total imaging time. The new classification and grading system allows a subtle description and suitable assessment of the articular cartilage repair tissue

Automatic multi-modal MR tissue classification for the assessment of response to bevacizumab in patients with glioblastoma

International Nuclear Information System (INIS)

Liberman, Gilad; Louzoun, Yoram; Aizenstein, Orna; Blumenthal, Deborah T.; Bokstein, Felix; Palmon, Mika; Corn, Benjamin W.; Ben Bashat, Dafna

2013-01-01

Background: Current methods for evaluation of treatment response in glioblastoma are inaccurate, limited and time-consuming. This study aimed to develop a multi-modal MRI automatic classification method to improve accuracy and efficiency of treatment response assessment in patients with recurrent glioblastoma (GB). Materials and methods: A modification of the k-Nearest-Neighbors (kNN) classification method was developed and applied to 59 longitudinal MR data sets of 13 patients with recurrent GB undergoing bevacizumab (anti-angiogenic) therapy. Changes in the enhancing tumor volume were assessed using the proposed method and compared with Macdonald's criteria and with manual volumetric measurements. The edema-like area was further subclassified into peri- and non-peri-tumoral edema, using both the kNN method and an unsupervised method, to monitor longitudinal changes. Results: Automatic classification using the modified kNN method was applicable in all scans, even when the tumors were infiltrative with unclear borders. The enhancing tumor volume obtained using the automatic method was highly correlated with manual measurements (N = 33, r = 0.96, p < 0.0001), while standard radiographic assessment based on Macdonald's criteria matched manual delineation and automatic results in only 68% of cases. A graded pattern of tumor infiltration within the edema-like area was revealed by both automatic methods, showing high agreement. All classification results were confirmed by a senior neuro-radiologist and validated using MR spectroscopy. Conclusion: This study emphasizes the important role of automatic tools based on a multi-modal view of the tissue in monitoring therapy response in patients with high grade gliomas specifically under anti-angiogenic therapy

Classification guide: Paralympic Games London 2012

OpenAIRE

2013-01-01

The London 2012 Paralympic Games Classification Guide is designed to provide National Paralympic Committees (NPCs) and International Paralympic Sport Federations (IPSFs) with information about the classification policies and procedures that will apply to the London 2012 Paralympic Games.

Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification

Directory of Open Access Journals (Sweden)

Eugene K. Lee

2017-11-01

Full Text Available Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC-derived cardiomyocytes and three-dimensional engineered cardiac tissue constructs to better recapitulate human heart function and drug responses. As these new platforms become increasingly sophisticated and high throughput, the drug screens result in larger multidimensional datasets. Improved automated analysis methods must therefore be developed in parallel to fully comprehend the cellular response across a multidimensional parameter space. Here, we describe the use of machine learning to comprehensively analyze 17 functional parameters derived from force readouts of hPSC-derived ventricular cardiac tissue strips (hvCTS electrically paced at a range of frequencies and exposed to a library of compounds. A generated metric is effective for then determining the cardioactivity of a given drug. Furthermore, we demonstrate a classification model that can automatically predict the mechanistic action of an unknown cardioactive drug.

Visualization and classification in biomedical terahertz pulsed imaging

International Nuclear Information System (INIS)

Loeffler, Torsten; Siebert, Karsten; Czasch, Stephanie; Bauer, Tobias; Roskos, Hartmut G

2002-01-01

'Visualization' in imaging is the process of extracting useful information from raw data in such a way that meaningful physical contrasts are developed. 'Classification' is the subsequent process of defining parameter ranges which allow us to identify elements of images such as different tissues or different objects. In this paper, we explore techniques for visualization and classification in terahertz pulsed imaging (TPI) for biomedical applications. For archived (formalin-fixed, alcohol-dehydrated and paraffin-mounted) test samples, we investigate both time- and frequency-domain methods based on bright- and dark-field TPI. Successful tissue classification is demonstrated

Classification System for Individualized Treatment of Adult Buried Penis Syndrome.

Science.gov (United States)

Tausch, Timothy J; Tachibana, Isamu; Siegel, Jordan A; Hoxworth, Ronald; Scott, Jeremy M; Morey, Allen F

2016-09-01

The authors present their experience with reconstructive strategies for men with various manifestations of adult buried penis syndrome, and propose a comprehensive anatomical classification system and treatment algorithm based on pathologic changes in the penile skin and involvement of neighboring abdominal and/or scrotal components. The authors reviewed all patients who underwent reconstruction of adult buried penis syndrome at their referral center between 2007 and 2015. Patients were stratified by location and severity of involved anatomical components. Procedures performed, demographics, comorbidities, and clinical outcomes were reviewed. Fifty-six patients underwent reconstruction of buried penis at the authors' center from 2007 to 2015. All procedures began with a ventral penile release. If the uncovered penile skin was determined to be viable, a phalloplasty was performed by anchoring penoscrotal skin to the proximal shaft, and the ventral shaft skin defect was closed with scrotal flaps. In more complex patients with circumferential nonviable penile skin, the penile skin was completely excised and replaced with a split-thickness skin graft. Complex patients with severe abdominal lipodystrophy required adjacent tissue transfer. For cases of genital lymphedema, the procedure involved complete excision of the lymphedematous tissue, and primary closure with or without a split-thickness skin graft, also often involving the scrotum. The authors' overall success rate was 88 percent (49 of 56), defined as resolution of symptoms without the need for additional procedures. Successful correction of adult buried penis often necessitates an interdisciplinary, multimodal approach. Therapeutic, IV.

Classification of breast tissue for protocols development in mammography exam;Classificacao dos tecidos mamarios para elaboracao de protocolos em exames de mamografia

Energy Technology Data Exchange (ETDEWEB)

Teixeira, M. Ines; Caldas, Linda V.E. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Chohfi, Adriana C.S.; Figueiredo, Zenaide A. [Universidade Nove de Julho (UNINOVE), Sao Paulo, SP (Brazil). Dept. da Saude. Radiologia Medica

2009-07-01

For accomplishment of a mammogram should be considered several factors such as equipment used and the classification of breast cancer patients. The density of the breast is different of patient to patient, thus making it difficult many precocious diagnostic of breast cancer. There is a significant variation in the breast to be radiographed, depending on several factors presented in the breast tissue of breast prosthesis with or without breasts or with implants. This work had as objective main to make a survey of the factors that influence in the classification of mammary fabrics. With this survey and classification it can be better adjusted the protocols which will be more efficient in the mammography exam, preventing excess of radiation dose, stress for the patient, economy of raw material, control of the quality and rapidity in the process of image attainment. (author)

Information gathering for CLP classification

Directory of Open Access Journals (Sweden)

Ida Marcello

2011-01-01

Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

A single simple procedure for dewaxing, hydration and heat-induced epitope retrieval (HIER) for immunohistochemistry in formalin fixed paraffin-embedded tissue

DEFF Research Database (Denmark)

Paulsen, I M S; Dimke, H; Frische, S

2015-01-01

Heat-induced epitope retrieval (HIER) is widely used for immunohistochemistry on formalin fixed paraffin-embedded tissue and includes temperatures well above the melting point of paraffin. We therefore tested whether traditional xylene-based removal of paraffin is required on sections from paraff...... of dewaxing in xylene. In conclusion, the HIER procedure described and tested can be used as a single procedure enabling dewaxing, hydration and epitope retrieval for immunohistochemistry in formalin fixed paraffin-embedded tissue....

A software tool for automatic classification and segmentation of 2D/3D medical images

International Nuclear Information System (INIS)

Strzelecki, Michal; Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur

2013-01-01

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided

A software tool for automatic classification and segmentation of 2D/3D medical images

Energy Technology Data Exchange (ETDEWEB)

Strzelecki, Michal, E-mail: michal.strzelecki@p.lodz.pl [Institute of Electronics, Technical University of Lodz, Wolczanska 211/215, 90-924 Lodz (Poland); Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur [Institute of Electronics, Technical University of Lodz, Wolczanska 211/215, 90-924 Lodz (Poland)

2013-02-21

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided.

Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomography.

Science.gov (United States)

Jeong, Jeong-Won; Shin, Dae C; Do, Synho; Marmarelis, Vasilis Z

2006-08-01

This paper presents a novel segmentation methodology for automated classification and differentiation of soft tissues using multiband data obtained with the newly developed system of high-resolution ultrasonic transmission tomography (HUTT) for imaging biological organs. This methodology extends and combines two existing approaches: the L-level set active contour (AC) segmentation approach and the agglomerative hierarchical kappa-means approach for unsupervised clustering (UC). To prevent the trapping of the current iterative minimization AC algorithm in a local minimum, we introduce a multiresolution approach that applies the level set functions at successively increasing resolutions of the image data. The resulting AC clusters are subsequently rearranged by the UC algorithm that seeks the optimal set of clusters yielding the minimum within-cluster distances in the feature space. The presented results from Monte Carlo simulations and experimental animal-tissue data demonstrate that the proposed methodology outperforms other existing methods without depending on heuristic parameters and provides a reliable means for soft tissue differentiation in HUTT images.

Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification.

Science.gov (United States)

Baczyńska, Anna K; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach's alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed.

DIF Trees: Using Classification Trees to Detect Differential Item Functioning

Science.gov (United States)

Vaughn, Brandon K.; Wang, Qiu

2010-01-01

A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel-Haenszel and logistic regression analysis. A nonparametric…

A minimum spanning forest based classification method for dedicated breast CT images

International Nuclear Information System (INIS)

Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei

2015-01-01

Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting model used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging

Classification guide: Sochi 2014 Paralympic Winter Games

OpenAIRE

2014-01-01

The Sochi 2014 Paralympic Winter Games classification guide is designed to provide National Paralympic Committees (NPCs) and International Federations (IFs) with information about the classification policies and procedures that will apply to the Sochi 2014 Paralympic Winter Games.

Clinically-inspired automatic classification of ovarian carcinoma subtypes

Directory of Open Access Journals (Sweden)

Aicha BenTaieb

2016-01-01

Full Text Available Context: It has been shown that ovarian carcinoma subtypes are distinct pathologic entities with differing prognostic and therapeutic implications. Histotyping by pathologists has good reproducibility, but occasional cases are challenging and require immunohistochemistry and subspecialty consultation. Motivated by the need for more accurate and reproducible diagnoses and to facilitate pathologists′ workflow, we propose an automatic framework for ovarian carcinoma classification. Materials and Methods: Our method is inspired by pathologists′ workflow. We analyse imaged tissues at two magnification levels and extract clinically-inspired color, texture, and segmentation-based shape descriptors using image-processing methods. We propose a carefully designed machine learning technique composed of four modules: A dissimilarity matrix, dimensionality reduction, feature selection and a support vector machine classifier to separate the five ovarian carcinoma subtypes using the extracted features. Results: This paper presents the details of our implementation and its validation on a clinically derived dataset of eighty high-resolution histopathology images. The proposed system achieved a multiclass classification accuracy of 95.0% when classifying unseen tissues. Assessment of the classifier′s confusion (confusion matrix between the five different ovarian carcinoma subtypes agrees with clinician′s confusion and reflects the difficulty in diagnosing endometrioid and serous carcinomas. Conclusions: Our results from this first study highlight the difficulty of ovarian carcinoma diagnosis which originate from the intrinsic class-imbalance observed among subtypes and suggest that the automatic analysis of ovarian carcinoma subtypes could be valuable to clinician′s diagnostic procedure by providing a second opinion.

The classification of benign and malignant human prostate tissue by multivariate analysis of {sup 1}H magnetic resonance spectra

Energy Technology Data Exchange (ETDEWEB)

Hahn, P.; Smith, I.; Leboldus, L.; Littman, C.; Somorjai, L.; Bezabeh, T. [Institute for Biodiagnostic, National Research Council, Manitoba (Canada)

1998-04-01

{sup 1}H magnetic resonance spectroscopy studies (360 MHz) were performed on specimens of benign (n = 66) and malignant (n = 21) human prostate tissue from 50 patients and the spectral data were subjected to multivariate analysis, specifically linear-discriminant analysis. On the basis of histopathological assessments, an overall classification accuracy of 96.6 % was achieved, with a sensitivity of 100 % and a specificity of 95.5 % in classifying benign prostatic hyperplasia from prostatic cancer. Resonances due to citrate, glutamate, and taurine were among the six spectral subregions identified by our algorithm as having diagnostic potential. Significantly higher levels of citrate were observed in glandular than in stromal benign prostatic hyperplasia (P < 0.05). This method shows excellent promise for the possibility of in vivo assessment of prostate tissue by magnetic resonance. (author)

Effective Exchange Rate Classifications and Growth

OpenAIRE

Justin M. Dubas; Byung-Joo Lee; Nelson C. Mark

2005-01-01

We propose an econometric procedure for obtaining de facto exchange rate regime classifications which we apply to study the relationship between exchange rate regimes and economic growth. Our classification method models the de jure regimes as outcomes of a multinomial logit choice problem conditional on the volatility of a country's effective exchange rate, a bilateral exchange rate and international reserves. An `effective' de facto exchange rate regime classification is then obtained by as...

Proteomic patterns analysis with multivariate calculations as a promising tool for prompt differentiation of early stage lung tissue with cancer and unchanged tissue material

Directory of Open Access Journals (Sweden)

Grodzki Tomasz

2011-03-01

Full Text Available Abstract Background Lung cancer diagnosis in tissue material with commonly used histological techniques is sometimes inconvenient and in a number of cases leads to ambiguous conclusions. Frequently advanced immunostaining techniques have to be employed, yet they are both time consuming and limited. In this study a proteomic approach is presented which may help provide unambiguous pathologic diagnosis of tissue material. Methods Lung tissue material found to be pathologically changed was prepared to isolate proteome with fast and non selective procedure. Isolated peptides and proteins in ranging from 3.5 to 20 kDa were analysed directly using high resolution mass spectrometer (MALDI-TOF/TOF with sinapic acid as a matrix. Recorded complex spectra of a single run were then analyzed with multivariate statistical analysis algorithms (principle component analysis, classification methods. In the applied protocol we focused on obtaining the spectra richest in protein signals constituting a pattern of change within the sample containing detailed information about its protein composition. Advanced statistical methods were to indicate differences between examined groups. Results Obtained results indicate changes in proteome profiles of changed tissues in comparison to physiologically unchanged material (control group which were reflected in the result of principle component analysis (PCA. Points representing spectra of control group were located in different areas of multidimensional space and were less diffused in comparison to cancer tissues. Three different classification algorithms showed recognition capability of 100% regarding classification of examined material into an appropriate group. Conclusion The application of the presented protocol and method enabled finding pathological changes in tissue material regardless of localization and size of abnormalities in the sample volume. Proteomic profile as a complex, rich in signals spectrum of proteins

Optical signature of nerve tissue-Exploratory ex vivo study comparing optical, histological, and molecular characteristics of different adipose and nerve tissues.

Science.gov (United States)

Balthasar, Andrea J R; Bydlon, Torre M; Ippel, Hans; van der Voort, Marjolein; Hendriks, Benno H W; Lucassen, Gerald W; van Geffen, Geert-Jan; van Kleef, Maarten; van Dijk, Paul; Lataster, Arno

2018-05-14

During several anesthesiological procedures, needles are inserted through the skin of a patient to target nerves. In most cases, the needle traverses several tissues-skin, subcutaneous adipose tissue, muscles, nerves, and blood vessels-to reach the target nerve. A clear identification of the target nerve can improve the success of the nerve block and reduce the rate of complications. This may be accomplished with diffuse reflectance spectroscopy (DRS) which can provide a quantitative measure of the tissue composition. The goal of the current study was to further explore the morphological, biological, chemical, and optical characteristics of the tissues encountered during needle insertion to improve future DRS classification algorithms. To compare characteristics of nerve tissue (sciatic nerve) and adipose tissues, the following techniques were used: histology, DRS, absorption spectrophotometry, high-resolution magic-angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy, and solution 2D 13 C- 1 H heteronuclear single-quantum coherence spectroscopy. Tissues from five human freshly frozen cadavers were examined. Histology clearly highlights a higher density of cellular nuclei, collagen, and cytoplasm in fascicular nerve tissue (IFAS). IFAS showed lower absorption of light around 1200 nm and 1750 nm, higher absorption around 1500 nm and 2000 nm, and a shift in the peak observed around 1000 nm. DRS measurements showed a higher water percentage and collagen concentration in IFAS and a lower fat percentage compared to all other tissues. The scattering parameter (b) was highest in IFAS. The HR-MAS NMR data showed three extra chemical peak shifts in IFAS tissue. Collagen, water, and cellular nuclei concentration are clearly different between nerve fascicular tissue and other adipose tissue and explain some of the differences observed in the optical absorption, DRS, and HR-NMR spectra of these tissues. Some differences observed between fascicular

New individual tissue compensators for high-energetic photons. Pt. 1. Principle and procedure

Energy Technology Data Exchange (ETDEWEB)

Quast, U; Krause, K [Essen Univ. (Gesamthochschule) (Germany, F.R.). Radiologisches Zentrum

1978-05-01

The inhomogeneity of absorbed dose caused by irregular body surface contour in the treatment port for external photon radiation is a problem. The discussion of the physical fundamentals and technical possibilities of missing tissue compensators leads to a practical solution. A new handy procedure is presented allowing easy and rapid preparing of geometrically minified as well as absorption- and stray radiation corrected individual compensators. The achievable dose homogeneity within the target volume is shown as better than +-5%. Systematical errors are investigated for the different parameters.

Proposal of a new classification scheme for periocular injuries

Directory of Open Access Journals (Sweden)

Devi Prasad Mohapatra

2017-01-01

Full Text Available Background: Eyelids are important structures and play a role in protecting the globe from trauma, brightness, in maintaining the integrity of tear films and moving the tears towards the lacrimal drainage system and contribute to aesthetic appearance of the face. Ophthalmic trauma is an important cause of morbidity among individuals and has also been responsible for additional cost of healthcare. Periocular trauma involving eyelids and adjacent structures has been found to have increased recently probably due to increased pace of life and increased dependence on machinery. A comprehensive classification of periocular trauma would help in stratifying these injuries as well as study outcomes. Material and Methods: This study was carried out at our institute from June 2015 to Dec 2015. We searched multiple English language databases for existing classification systems for periocular trauma. We designed a system of classification of periocular soft tissue injuries based on clinico-anatomical presentations. This classification was applied prospectively to patients presenting with periocular soft tissue injuries to our department. Results: A comprehensive classification scheme was designed consisting of five types of periocular injuries. A total of 38 eyelid injuries in 34 patients were evaluated in this study. According to the System for Peri-Ocular Trauma (SPOT classification, Type V injuries were most common. SPOT Type II injuries were more common isolated injuries among all zones. Discussion: Classification systems are necessary in order to provide a framework in which to scientifically study the etiology, pathogenesis, and treatment of diseases in an orderly fashion. The SPOT classification has taken into account the periocular soft tissue injuries i.e., upper eyelid, lower eyelid, medial and lateral canthus injuries., based on observed clinico-anatomical patterns of eyelid injuries. Conclusion: The SPOT classification seems to be a reliable

Histopathological examination of tissue resected during bariatric procedures - to be done or not to be done?

Science.gov (United States)

Walędziak, Maciej; Różańska-Walędziak, Anna; Kowalewski, Piotr K; Janik, Michał R; Paśnik, Krzysztof

2017-06-01

Obesity is one of the major lifestyle diseases and provokes various comorbidities, such as hypertension, type 2 diabetes mellitus, obstructive sleep apnea, and even neoplasms. Bariatric surgery is the most effective treatment of obesity. Since cost-effectiveness has become a major concern, there is a tendency to avoid general histological evaluation of surgical specimens during routine procedures. To evaluate the necessity of histopathological investigation of tissue excised during bariatric surgery and to verify whether the operation should be continued in the case of suspicious macroscopic findings. From January 2013 to December 2016, 1252 patients with obesity were qualified for bariatric procedures. The qualification was performed according to the current European recommendations. Every operation started with an inspection of the peritoneal cavity performed once the abdomen was insufflated. If a macroscopic pathology was found, the specimen was secured for histopathological investigation. Out of 81 (6.47%) patients from whom histopathological samples were collected, 39% (n = 32) showed negative results, and 61% (n = 49) cases showed abnormalities. As it is impossible to exclude the existence of gastric tumors only in preoperative gastroscopy and ultrasonography, especially as there is a higher risk in obese patients, routine histological examination of tissue excised during bariatric procedures should be considered. Since most of the neoplasms were found to be benign, there is no need to abandon the bariatric procedure if a pathology is found and resected. Bariatric surgeons should always focus on thorough examination of the abdominal and the pelvic cavity, especially in female patients.

Classification of first branchial cleft anomalies: is it clinically relevant ...

African Journals Online (AJOL)

Background: There are three classification systems for first branchial cleft anomalies currently in use. The Arnot, Work and Olsen classifications describe these lesions on the basis of morphology, tissue of origin and clinical appearance. However, the clinical relevance of these classifications is debated, as they may not be ...

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

Science.gov (United States)

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies.

Directory of Open Access Journals (Sweden)

Xingjie Hao

2018-01-01

Full Text Available Genome-wide association studies (GWASs have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART. With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study.

Tissue encapsulation of the proximal Essure micro-insert from the uterine cavity following hysteroscopic sterilization.

Science.gov (United States)

Kerin, John F; Munday, David; Ritossa, Martin; Rosen, David

2007-01-01

To assess the interaction between the trailing ends of a sterilization micro-insert extending into the uterine cavity and the surrounding uterine tissue environment over time. Multicenter, retrospective observational study (Canadian Task Force classification II-1). Hospital-based clinical research centers. A subset of a study population of 545 women who had undergone a hysteroscopic sterilization procedure. A second-look hysteroscopy was performed in 22 (20 with uterine bleeding, 2 pre IVF) of these 545 women between 4 and 43 months from the sterilization procedure. Over a mean time period of 19.73 months, the trailing coils of the micro-inserts into the uterine cavity shortened from a mean of 5.7 mm to 2.0 mm and from 5.4 mm to 1.8 mm on the right and left sides, respectively. In cases observed within 12 months or fewer post-procedure, the complete tissue encapsulation of both micro-inserts had already occurred in 17% of the observations. Among cases evaluated from 13 to 43 months post-procedure, 25% evidenced complete encapsulation. Two mechanisms appear to be responsible for this process. First, there is an initial mechanical "winding-in" of the micro-insert of approximately 1 rotation of its outer coil, accounting for 1 mm of its length, after release from its delivery system. Second, the tissue around the ostium appears to use the trailing coils of the micro-insert as a scaffolding structure, gradually encapsulating and excluding them from the uterine cavity. The gradual tissue exclusion of the micro-insert from the uterine cavity may make it pregnancy-compatible after in vitro fertilization and embryo transfer procedures.

Maxillectomy defects: a suggested classification scheme.

Science.gov (United States)

Akinmoladun, V I; Dosumu, O O; Olusanya, A A; Ikusika, O F

2013-06-01

The term "maxillectomy" has been used to describe a variety of surgical procedures for a spectrum of diseases involving a diverse anatomical site. Hence, classifications of maxillectomy defects have often made communication difficult. This article highlights this problem, emphasises the need for a uniform system of classification and suggests a classification system which is simple and comprehensive. Articles related to this subject, especially those with specified classifications of maxillary surgical defects were sourced from the internet through Google, Scopus and PubMed using the search terms maxillectomy defects classification. A manual search through available literature was also done. The review of the materials revealed many classifications and modifications of classifications from the descriptive, reconstructive and prosthodontic perspectives. No globally acceptable classification exists among practitioners involved in the management of diseases in the mid-facial region. There were over 14 classifications of maxillary defects found in the English literature. Attempts made to address the inadequacies of previous classifications have tended to result in cumbersome and relatively complex classifications. A single classification that is based on both surgical and prosthetic considerations is most desirable and is hereby proposed.

Updated Lagrangian finite element formulations of various biological soft tissue non-linear material models: a comprehensive procedure and review.

Science.gov (United States)

Townsend, Molly T; Sarigul-Klijn, Nesrin

2016-01-01

Simplified material models are commonly used in computational simulation of biological soft tissue as an approximation of the complicated material response and to minimize computational resources. However, the simulation of complex loadings, such as long-duration tissue swelling, necessitates complex models that are not easy to formulate. This paper strives to offer the updated Lagrangian formulation comprehensive procedure of various non-linear material models for the application of finite element analysis of biological soft tissues including a definition of the Cauchy stress and the spatial tangential stiffness. The relationships between water content, osmotic pressure, ionic concentration and the pore pressure stress of the tissue are discussed with the merits of these models and their applications.

Optimization of wet digestion procedure of blood and tissue for selenium determination by means of 75Se tracer

International Nuclear Information System (INIS)

Holynska, B.; Lipinska-Kalita, K.

1977-01-01

Selenium-75 tracer has been used for optimization of analytical procedure of selenium determination in blood and tissue. Wet digestion procedure and reduction of selenium to its elemental form with tellurium as coprecipitant have been tested. It is seen that the use of a mixture of perchloric and sulphuric acid with sodium molybdenate for the wet digestion of organic matter followed by the reduction of selenium to its elementary form by a mixture of stannous chloride and hydroxylamine hydrochloride results in very good recovery of selenium. Recovery of selenium obtained with the use of optimized analytical procedure amounts to 95% and precision is equal to 4.2%. (T.I.)

Analytical Procedures for Testability.

Science.gov (United States)

1983-01-01

Beat Internal Classifications", AD: A018516. "A System of Computer Aided Diagnosis with Blood Serum Chemistry Tests and Bayesian Statistics", AD: 786284...6 LIST OF TALS .. 1. Truth Table ......................................... 49 2. Covering Problem .............................. 93 3. Primary and...quential classification procedure in a coronary care ward is evaluated. In the toxicology field "A System of Computer Aided Diagnosis with Blood Serum

A comparison of the Web of Science with publication-level classification systems of science

Energy Technology Data Exchange (ETDEWEB)

Perianes-Rodriguez, A.; Ruiz-Castillo, J.

2016-07-01

In this paper we propose a new criterion for choosing between a pair of classification systems of science that assign publications (or journals) to a set of scientific fields. Consider the standard normalization procedure in which field mean citations are used as normalization factors. We recommend system A over system B whenever the standard normalization procedure based on A performs better than the when it is based on B. Since the evaluation can be made in terms of either system, the performance assessment requires a double test. In addition, since the assessment of two normalization procedures would be generally biased in favor of the one based on the classification system used for evaluation purposes, ideally a pair of classification systems must be compared using a third, independent classification system for evaluation purposes. We illustrate this strategy by comparing a Web of Science journal-level classification system, consisting of 236 journal subject categories, with two publication-level algorithmically constructed classification systems consisting of 1,363 (G6) and 5,119 (G8) clusters. There are two main findings. (1) The G8 system is found to dominate the G6 system. Therefore, when we have a choice between two classification systems at different granularity levels, we should use the system at the higher level because it typically exhibits a better standard normalization performance. (2) The G8 system and the Web of Science (WoS) journal-level system are found to be non-comparable. Nevertheless, the G8-normalization procedure performs better using the WoS system for evaluation purposes than the WoS-normalization procedure using the G8 system for evaluation purposes. Furthermore, when we use the G6 system for evaluation purposes, the G8-normalization procedure performs better than the WoS-normalization procedure. We conclude that algorithmically constructed classification systems constitute a credible alternative to the WoS system and, by extension, to

European Organisation for Research and Treatment of Cancer (EORTC) Pathobiology Group standard operating procedure for the preparation of human tumour tissue extracts suited for the quantitative analysis of tissue-associated biomarkers.

Science.gov (United States)

Schmitt, Manfred; Mengele, Karin; Schueren, Elisabeth; Sweep, Fred C G J; Foekens, John A; Brünner, Nils; Laabs, Juliane; Malik, Abha; Harbeck, Nadia

2007-03-01

With the new concept of 'individualized treatment and targeted therapies', tumour tissue-associated biomarkers have been given a new role in selection of cancer patients for treatment and in cancer patient management. Tumour biomarkers can give support to cancer patient stratification and risk assessment, treatment response identification, or to identifying those patients who are expected to respond to certain anticancer drugs. As the field of tumour-associated biomarkers has expanded rapidly over the last years, it has become increasingly apparent that a strong need exists to establish guidelines on how to easily disintegrate the tumour tissue for assessment of the presence of tumour tissue-associated biomarkers. Several mechanical tissue (cell) disruption techniques exist, ranging from bead mill homogenisation and freeze-fracturing through to blade or pestle-type homogenisation, to grinding and ultrasonics. Still, only a few directives have been given on how fresh-frozen tumour tissues should be processed for the extraction and determination of tumour biomarkers. The PathoBiology Group of the European Organisation for Research and Treatment of Cancer therefore has devised a standard operating procedure for the standardised preparation of human tumour tissue extracts which is designed for the quantitative analysis of tumour tissue-associated biomarkers. The easy to follow technical steps involved require 50-300 mg of deep-frozen cancer tissue placed into small size (1.2 ml) cryogenic tubes. These are placed into the shaking flask of a Mikro-Dismembrator S machine (bead mill) to pulverise the tumour tissue in the capped tubes in the deep-frozen state by use of a stainless steel ball, all within 30 s of exposure. RNA is isolated from the pulverised tissue following standard procedures. Proteins are extracted from the still frozen pulverised tissue by addition of Tris-buffered saline to obtain the cytosol fraction of the tumour or by the Tris buffer supplemented with

28 CFR 527.31 - Procedures.

Science.gov (United States)

2010-07-01

... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Procedures. 527.31 Section 527.31 Judicial Administration BUREAU OF PRISONS, DEPARTMENT OF JUSTICE INMATE ADMISSION, CLASSIFICATION, AND TRANSFER TRANSFERS Transfer of Inmates to State Agents for Production on State Writs § 527.31 Procedures...

Rock suitability classification RSC 2012

Energy Technology Data Exchange (ETDEWEB)

McEwen, T. (ed.) [McEwen Consulting, Leicester (United Kingdom); Kapyaho, A. [Geological Survey of Finland, Espoo (Finland); Hella, P. [Saanio and Riekkola, Helsinki (Finland); Aro, S.; Kosunen, P.; Mattila, J.; Pere, T.

2012-12-15

This report presents Posiva's Rock Suitability Classification (RSC) system, developed for locating suitable rock volumes for repository design and construction. The RSC system comprises both the revised rock suitability criteria and the procedure for the suitability classification during the construction of the repository. The aim of the classification is to avoid such features of the host rock that may be detrimental to the favourable conditions within the repository, either initially or in the long term. This report also discusses the implications of applying the RSC system for the fulfilment of the regulatory requirements concerning the host rock as a natural barrier and the site's overall suitability for hosting a final repository of spent nuclear fuel.

Rock suitability classification RSC 2012

International Nuclear Information System (INIS)

McEwen, T.; Kapyaho, A.; Hella, P.; Aro, S.; Kosunen, P.; Mattila, J.; Pere, T.

2012-12-01

This report presents Posiva's Rock Suitability Classification (RSC) system, developed for locating suitable rock volumes for repository design and construction. The RSC system comprises both the revised rock suitability criteria and the procedure for the suitability classification during the construction of the repository. The aim of the classification is to avoid such features of the host rock that may be detrimental to the favourable conditions within the repository, either initially or in the long term. This report also discusses the implications of applying the RSC system for the fulfilment of the regulatory requirements concerning the host rock as a natural barrier and the site's overall suitability for hosting a final repository of spent nuclear fuel

An Adaptive Landscape Classification Procedure using Geoinformatics and Artificial Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Coleman, Andre Michael [Vrije Univ., Amsterdam (Netherlands)

2008-06-01

The Adaptive Landscape Classification Procedure (ALCP), which links the advanced geospatial analysis capabilities of Geographic Information Systems (GISs) and Artificial Neural Networks (ANNs) and particularly Self-Organizing Maps (SOMs), is proposed as a method for establishing and reducing complex data relationships. Its adaptive and evolutionary capability is evaluated for situations where varying types of data can be combined to address different prediction and/or management needs such as hydrologic response, water quality, aquatic habitat, groundwater recharge, land use, instrumentation placement, and forecast scenarios. The research presented here documents and presents favorable results of a procedure that aims to be a powerful and flexible spatial data classifier that fuses the strengths of geoinformatics and the intelligence of SOMs to provide data patterns and spatial information for environmental managers and researchers. This research shows how evaluation and analysis of spatial and/or temporal patterns in the landscape can provide insight into complex ecological, hydrological, climatic, and other natural and anthropogenic-influenced processes. Certainly, environmental management and research within heterogeneous watersheds provide challenges for consistent evaluation and understanding of system functions. For instance, watersheds over a range of scales are likely to exhibit varying levels of diversity in their characteristics of climate, hydrology, physiography, ecology, and anthropogenic influence. Furthermore, it has become evident that understanding and analyzing these diverse systems can be difficult not only because of varying natural characteristics, but also because of the availability, quality, and variability of spatial and temporal data. Developments in geospatial technologies, however, are providing a wide range of relevant data, and in many cases, at a high temporal and spatial resolution. Such data resources can take the form of high

Learning semantic histopathological representation for basal cell carcinoma classification

Science.gov (United States)

Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

2013-03-01

Diagnosis of a histopathology glass slide is a complex process that involves accurate recognition of several structures, their function in the tissue and their relation with other structures. The way in which the pathologist represents the image content and the relations between those objects yields a better and accurate diagnoses. Therefore, an appropriate semantic representation of the image content will be useful in several analysis tasks such as cancer classification, tissue retrieval and histopahological image analysis, among others. Nevertheless, to automatically recognize those structures and extract their inner semantic meaning are still very challenging tasks. In this paper we introduce a new semantic representation that allows to describe histopathological concepts suitable for classification. The approach herein identify local concepts using a dictionary learning approach, i.e., the algorithm learns the most representative atoms from a set of random sampled patches, and then models the spatial relations among them by counting the co-occurrence between atoms, while penalizing the spatial distance. The proposed approach was compared with a bag-of-features representation in a tissue classification task. For this purpose, 240 histological microscopical fields of view, 24 per tissue class, were collected. Those images fed a Support Vector Machine classifier per class, using 120 images as train set and the remaining ones for testing, maintaining the same proportion of each concept in the train and test sets. The obtained classification results, averaged from 100 random partitions of training and test sets, shows that our approach is more sensitive in average than the bag-of-features representation in almost 6%.

Classification of parotidectomy: a proposed modification to the European Salivary Gland Society classification system.

Science.gov (United States)

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

Parotidectomy remains the mainstay of treatment for both benign and malignant lesions of the parotid gland. There exists a wide range of possible surgical options in parotidectomy in terms of extent of parotid tissue removed. There is increasing need for uniformity of terminology resulting from growing interest in modifications of the conventional parotidectomy. It is, therefore, of paramount importance for a standardized classification system in describing extent of parotidectomy. Recently, the European Salivary Gland Society (ESGS) proposed a novel classification system for parotidectomy. The aim of this study is to evaluate this system. A classification system proposed by the ESGS was critically re-evaluated and modified to increase its accuracy and its acceptability. Modifications mainly focused on subdividing Levels I and II into IA, IB, IIA, and IIB. From June 2006 to June 2016, 126 patients underwent 130 parotidectomies at our hospital. The classification system was tested in that cohort of patient. While the ESGS classification system is comprehensive, it does not cover all possibilities. The addition of Sublevels IA, IB, IIA, and IIB may help to address some of the clinical situations seen and is clinically relevant. We aim to test the modified classification system for partial parotidectomy to address some of the challenges mentioned.

Lattice classification of the four-dimensional heterotic strings

International Nuclear Information System (INIS)

Balog, J.; Forgacs, P.; Vecsernyes, P.; Horvath, Z.

1987-06-01

A lattice slicing procedure is proposed which leads to the classification of all four-dimensional chiral heterotic strings based on Conway and Sloane's 22-dimensional self-dual Euclidean lattices. By reversing this procedure it is possible to construct all these theories. (author)

Evaluation of thyroid tissue by Raman spectroscopy

Science.gov (United States)

Teixeira, C. S. B.; Bitar, R. A.; Santos, A. B. O.; Kulcsar, M. A. V.; Friguglietti, C. U. M.; Martinho, H. S.; da Costa, R. B.; Martin, A. A.

2010-02-01

Thyroid gland is a small gland in the neck consisting of two lobes connected by an isthmus. Thyroid's main function is to produce the hormones thyroxine (T4), triiodothyronine (T3) and calcitonin. Thyroid disorders can disturb the production of these hormones, which will affect numerous processes within the body such as: regulating metabolism and increasing utilization of cholesterol, fats, proteins, and carbohydrates. The gland itself can also be injured; for example, neoplasias, which have been considered the most important, causing damage of to the gland and are difficult to diagnose. There are several types of thyroid cancer: Papillary, Follicular, Medullary, and Anaplastic. The occurrence rate, in general is between 4 and 7%; which is on the increase (30%), probably due to new technology that is able to find small thyroid cancers that may not have been found previously. The most common method used for thyroid diagnoses are: anamnesis, ultrasonography, and laboratory exams (Fine Needle Aspiration Biopsy- FNAB). However, the sensitivity of those test are rather poor, with a high rate of false-negative results, therefore there is an urgent need to develop new diagnostic techniques. Raman spectroscopy has been presented as a valuable tool for cancer diagnosis in many different tissues. In this work, 27 fragments of the thyroid were collected from 18 patients, comprising the following histologic groups: goitre adjacent tissue, goitre nodular tissue, follicular adenoma, follicular carcinoma, and papillary carcinoma. Spectral collection was done with a commercial FTRaman Spectrometer (Bruker RFS100/S) using a 1064 nm laser excitation and Ge detector. Principal Component Analysis, Cluster Analysis, and Linear Discriminant Analysis with cross-validation were applied as spectral classification algorithm. Comparing the goitre adjacent tissue with the goitre nodular region, an index of 58.3% of correct classification was obtained. Between goitre (nodular region and

Nuclear power plant systems, structures and components and their safety classification

International Nuclear Information System (INIS)

2000-01-01

The assurance of a nuclear power plant's safety is based on the reliable functioning of the plant as well as on its appropriate maintenance and operation. To ensure the reliability of operation, special attention shall be paid to the design, manufacturing, commissioning and operation of the plant and its components. To control these functions the nuclear power plant is divided into structural and functional entities, i.e. systems. A systems safety class is determined by its safety significance. Safety class specifies the procedures to be employed in plant design, construction, monitoring and operation. The classification document contains all documentation related to the classification of the nuclear power plant. The principles of safety classification and the procedures pertaining to the classification document are presented in this guide. In the Appendix of the guide, examples of systems most typical of each safety class are given to clarify the safety classification principles

Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes.

Science.gov (United States)

Cannistraci, Carlo Vittorio; Ravasi, Timothy; Montevecchi, Franco Maria; Ideker, Trey; Alessio, Massimo

2010-09-15

Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. 'Minimum Curvilinearity' (MC) is a principle that-for small datasets-suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. https://sites.google.com/site/carlovittoriocannistraci/home.

Three-class classification in computer-aided diagnosis of breast cancer by support vector machine

Science.gov (United States)

Sun, Xuejun; Qian, Wei; Song, Dansheng

2004-05-01

Design of classifier in computer-aided diagnosis (CAD) scheme of breast cancer plays important role to its overall performance in sensitivity and specificity. Classification of a detected object as malignant lesion, benign lesion, or normal tissue on mammogram is a typical three-class pattern recognition problem. This paper presents a three-class classification approach by using two-stage classifier combined with support vector machine (SVM) learning algorithm for classification of breast cancer on mammograms. The first classification stage is used to detect abnormal areas and normal breast tissues, and the second stage is for classification of malignant or benign in detected abnormal objects. A series of spatial, morphology and texture features have been extracted on detected objects areas. By using genetic algorithm (GA), different feature groups for different stage classification have been investigated. Computerized free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) analyses have been employed in different classification stages. Results have shown that obvious performance improvement in both sensitivity and specificity was observed through proposed classification approach compared with conventional two-class classification approaches, indicating its effectiveness in classification of breast cancer on mammograms.

Identification of immune cell infiltration in hematoxylin-eosin stained breast cancer samples: texture-based classification of tissue morphologies

Science.gov (United States)

Turkki, Riku; Linder, Nina; Kovanen, Panu E.; Pellinen, Teijo; Lundin, Johan

2016-03-01

The characteristics of immune cells in the tumor microenvironment of breast cancer capture clinically important information. Despite the heterogeneity of tumor-infiltrating immune cells, it has been shown that the degree of infiltration assessed by visual evaluation of hematoxylin-eosin (H and E) stained samples has prognostic and possibly predictive value. However, quantification of the infiltration in H and E-stained tissue samples is currently dependent on visual scoring by an expert. Computer vision enables automated characterization of the components of the tumor microenvironment, and texture-based methods have successfully been used to discriminate between different tissue morphologies and cell phenotypes. In this study, we evaluate whether local binary pattern texture features with superpixel segmentation and classification with support vector machine can be utilized to identify immune cell infiltration in H and E-stained breast cancer samples. Guided with the pan-leukocyte CD45 marker, we annotated training and test sets from 20 primary breast cancer samples. In the training set of arbitrary sized image regions (n=1,116) a 3-fold cross-validation resulted in 98% accuracy and an area under the receiver-operating characteristic curve (AUC) of 0.98 to discriminate between immune cell -rich and - poor areas. In the test set (n=204), we achieved an accuracy of 96% and AUC of 0.99 to label cropped tissue regions correctly into immune cell -rich and -poor categories. The obtained results demonstrate strong discrimination between immune cell -rich and -poor tissue morphologies. The proposed method can provide a quantitative measurement of the degree of immune cell infiltration and applied to digitally scanned H and E-stained breast cancer samples for diagnostic purposes.

Integrated and convenient procedure for protein extraction from formalin-fixed, paraffin-embedded tissues for LC-MS/MS analysis.

Science.gov (United States)

Lai, Xianyin; Schneider, Bryan P

2014-11-01

Because fresh-frozen tissue samples associated with long-term clinical data and of rare diseases are often unobtainable at the present time, formalin-fixed paraffin-embedded (FFPE) tissue samples are considered a highly valuable resource for researchers. However, protein extraction from FFPE tissues faces challenges of deparaffinization and cross-link reversion. Current procedures for protein extraction from FFPE tissue require separate steps and toxic solvents, resulting in inconvenience in protein extraction. To overcome these limitations, an integrated method was developed using nontoxic solvents in four types of FFPE tissues. The average amount of proteins from three replicates of bladder, kidney, liver, and lung FFPE tissues were 442.6, 728.9, 736.4, and 694.7 μg with CVs of 7.5, 5.8, 2.4, and 4.5%, respectively. Proteomic analysis showed that 348, 417, 607, and 304 unique proteins were identified and quantified without specification of isoform by a least two peptides from bladder, kidney, liver, and lung FFPE tissue samples, respectively. The analysis of individual protein CV demonstrated that 97-99% of the proteins were quantified with a CV ≤ 30%, verifying the reproducibility of the integrated protein extraction method. In summary, the developed method is high-yield, reproducible, convenient, simple, low cost, nonvolatile, nonflammable, and nontoxic. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Use of a Fresh-Tissue Cadaver Model for the Instruction of Dermatological Procedures: A Laboratory Study for Training Medical Students.

Science.gov (United States)

Cervantes, Jose A; Costello, Collin M; Maarouf, Melody; McCrary, Hilary C; Zeitouni, Nathalie C

2017-09-01

A realistic model for the instruction of basic dermatologic procedural skills was developed, while simultaneously increasing medical student exposure to the field of dermatology. The primary purpose of the authors' study was to evaluate the utilization of a fresh-tissue cadaver model (FTCM) as a method for the instruction of common dermatologic procedures. The authors' secondary aim was to assess students' perceived clinical skills and overall perception of the field of dermatology after the lab. Nineteen first- and second-year medical students were pre- and post-tested on their ability to perform punch and excisional biopsies on a fresh-tissue cadaver. Students were then surveyed on their experience. Assessment of the cognitive knowledge gain and technical skills revealed a statistically significant improvement in all categories (p < .001). An analysis of the survey demonstrated that 78.9% were more interested in selecting dermatology as a career and 63.2% of participants were more likely to refer their future patients to a Mohs surgeon. An FTCM is a viable method for the instruction and training of dermatologic procedures. In addition, the authors conclude that an FTCM provides realistic instruction for common dermatologic procedures and enhances medical students' early exposure and interest in the field of dermatology.

Using Procedure Based on Item Response Theory to Evaluate Classification Consistency Indices in the Practice of Large-Scale Assessment

Directory of Open Access Journals (Sweden)

Shanshan Zhang

2017-09-01

Full Text Available In spite of the growing interest in the methods of evaluating the classification consistency (CC indices, only few researches are available in the field of applying these methods in the practice of large-scale educational assessment. In addition, only few studies considered the influence of practical factors, for example, the examinee ability distribution, the cut score location and the score scale, on the performance of CC indices. Using the newly developed Lee's procedure based on the item response theory (IRT, the main purpose of this study is to investigate the performance of CC indices when practical factors are taken into consideration. A simulation study and an empirical study were conducted under comprehensive conditions. Results suggested that with negatively skewed distribution, the CC indices were larger than with other distributions. Interactions occurred among ability distribution, cut score location, and score scale. Consequently, Lee's IRT procedure is reliable to be used in the field of large-scale educational assessment, and when reporting the indices, it should be treated with caution as testing conditions may vary a lot.

Added soft tissue contrast using signal attenuation and the fractal dimension for optical coherence tomography images of porcine arterial tissue

International Nuclear Information System (INIS)

Flueraru, C; Mao, Y; Chang, S; Popescu, D P; Sowa, M G

2010-01-01

Optical coherence tomography (OCT) images of left-descending coronary tissues harvested from three porcine specimens were acquired with a home-build swept-source OCT setup. Despite the fact that OCT is capable of acquiring high resolution circumferential images of vessels, many distinct histological features of a vessel have comparable optical properties leading to poor contrast in OCT images. Two classification methods were tested in this report for the purpose of enhancing contrast between soft-tissue components of porcine coronary vessels. One method involved analyzing the attenuation of the OCT signal as a function of light penetration into the tissue. We demonstrated that by analyzing the signal attenuation in this manner we were able to differentiate two media sub-layers with different orientations of the smooth muscle cells. The other classification method used in our study was fractal analysis. Fractal analysis was implemented in a box-counting (fractal dimension) image-processing code and was used as a tool to differentiate and quantify variations in tissue texture at various locations in the OCT images. The calculated average fractal dimensions had different values in distinct regions of interest (ROI) within the imaged coronary samples. When compared to the results obtained by using the attenuation of the OCT signal, the method of fractal analysis demonstrated better classification potential for distinguishing amongst the tissue ROI.

New guidelines for dam safety classification

International Nuclear Information System (INIS)

Dascal, O.

1999-01-01

Elements are outlined of recommended new guidelines for safety classification of dams. Arguments are provided for the view that dam classification systems should require more than one system as follows: (a) classification for selection of design criteria, operation procedures and emergency measures plans, based on potential consequences of a dam failure - the hazard classification of water retaining structures; (b) classification for establishment of surveillance activities and for safety evaluation of dams, based on the probability and consequences of failure - the risk classification of water retaining structures; and (c) classification for establishment of water management plans, for safety evaluation of the entire project, for preparation of emergency measures plans, for definition of the frequency and extent of maintenance operations, and for evaluation of changes and modifications required - the hazard classification of the project. The hazard classification of the dam considers, as consequence, mainly the loss of lives or persons in jeopardy and the property damages to third parties. Difficulties in determining the risk classification of the dam lie in the fact that no tool exists to evaluate the probability of the dam's failure. To overcome this, the probability of failure can be substituted for by a set of dam characteristics that express the failure potential of the dam and its foundation. The hazard classification of the entire project is based on the probable consequences of dam failure influencing: loss of life, persons in jeopardy, property and environmental damage. The classification scheme is illustrated for dam threatening events such as earthquakes and floods. 17 refs., 5 tabs

Standard Operating Procedure (SOP) for Rapid and Efficient Production of Stevia Tissue Culture Seedlings

International Nuclear Information System (INIS)

Norazlina Noordin; Peng, C.S.; Rusli Ibrahim

2015-01-01

Stevia rebaudiana Bertoni is a non-caloric natural sweetener which is 300 times sweeter than cane sugar. Extracts from stevia leaves has vast application in food and beverages based industries, can be added to tea and coffee, cooked or baked goods, processed foods and confectionary goods. Recently, stevia attained awareness owing to its natural, non-caloric sweetness by diet/ health conscious and diabetic persons (Arpita et al., 2011). This natural sweetener has high commercial value in global market, it was estimated that global market value for stevia is be around USD11 billion by year 2015. Although stevia is being largely popularized in Malaysia and other countries but large-scale propagation procedures for the continuous supply of planting materials in commercial plantation has yet to be established, optimized and standardized. Furthermore, propagation through stevia seeds is often very difficult due to self-incompatibility which results in sterile seeds (Sakaguchi et al., 1982). Tissue culture is the only rapid process for the mass propagation of stevia and there have been few reports of in vitro growth of stevia (Miyagaya et al., 1986) and in vitro micropropagation from shoot tip and leaf (Uddin et al., 2006). Hence, study was carried out to establish a suitable protocol for in vitro propagation of S. rebaudiana Bertoni that can be further up-scaled for mass propagation of stevia seedlings. The established Standard Operating Procedure (SOP) will ensure rapid and efficient production of stevia tissue culture seedlings for continuous supply of planting materials for commercial stevia plantations in Malaysia. Preparation of growth medium, multiplication of shoots, rooting of plant lets and hardening of ex-vitro rooted plant lets is discussed in this paper. (author)

Advances in the classification and treatment of mastocytosis

DEFF Research Database (Denmark)

Valent, Peter; Akin, Cem; Hartmann, Karin

2017-01-01

Mastocytosis is a term used to denote a heterogeneous group of conditions defined by the expansion and accumulation of clonal (neoplastic) tissue mast cells in various organs. The classification of the World Health Organization (WHO) divides the disease into cutaneous mastocytosis, systemic...... leukemia. The clinical impact and prognostic value of this classification has been confirmed in numerous studies, and its basic concept remains valid. However, refinements have recently been proposed by the consensus group, the WHO, and the European Competence Network on Mastocytosis. In addition, new...... of mastocytosis, with emphasis on classification, prognostication, and emerging new treatment options in advanced systemic mastocytosis....

Projected estimators for robust semi-supervised classification

DEFF Research Database (Denmark)

Krijthe, Jesse H.; Loog, Marco

2017-01-01

For semi-supervised techniques to be applied safely in practice we at least want methods to outperform their supervised counterparts. We study this question for classification using the well-known quadratic surrogate loss function. Unlike other approaches to semi-supervised learning, the procedure...... specifically, we prove that, measured on the labeled and unlabeled training data, this semi-supervised procedure never gives a lower quadratic loss than the supervised alternative. To our knowledge this is the first approach that offers such strong, albeit conservative, guarantees for improvement over...... the supervised solution. The characteristics of our approach are explicated using benchmark datasets to further understand the similarities and differences between the quadratic loss criterion used in the theoretical results and the classification accuracy typically considered in practice....

Imaging the spectral reflectance properties of bipolar radiofrequency-fused bowel tissue

Science.gov (United States)

Clancy, Neil T.; Arya, Shobhit; Stoyanov, Danail; Du, Xiaofei; Hanna, George B.; Elson, Daniel S.

2015-07-01

Delivery of radiofrequency (RF) electrical energy is used during surgery to heat and seal tissue, such as vessels, allowing resection without blood loss. Recent work has suggested that this approach may be extended to allow surgical attachment of larger tissue segments for applications such as bowel anastomosis. In a large series of porcine surgical procedures bipolar RF energy was used to resect and re-seal the small bowel in vivo with a commercial tissue fusion device (Ligasure; Covidien PLC, USA). The tissue was then imaged with a multispectral imaging laparoscope to obtain a spectral datacube comprising both fused and healthy tissue. Maps of blood volume, oxygen saturation and scattering power were derived from the measured reflectance spectra using an optimised light-tissue interaction model. A 60% increase in reflectance of visible light (460-700 nm) was observed after fusion, with the tissue taking on a white appearance. Despite this the distinctive shape of the haemoglobin absorption spectrum was still noticeable in the 460-600 nm wavelength range. Scattering power increased in the fused region in comparison to normal serosa, while blood volume and oxygen saturation decreased. Observed fusion-induced changes in the reflectance spectrum are consistent with the biophysical changes induced through tissue denaturation and increased collagen cross-linking. The multispectral imager allows mapping of the spatial extent of these changes and classification of the zone of damaged tissue. Further analysis of the spectral data in parallel with histopathological examination of excised specimens will allow correlation of the optical property changes with microscopic alterations in tissue structure.

General and selective isolation procedure for high-performance liquid chromatographic determination of anabolic steroids in tissues.

Science.gov (United States)

Laganà, A; Marino, A

1991-12-27

A multi-residue method has been developed for the determination of anabolic steroids in animal tissue. The analytes are extracted from tissue with methanol and the extract is subjected to two solid-phase extractions, one using a non-specific adsorbing material, such as graphitized carbon black (Carbopack B), and the other Amberlite CG-400 I in the OH form. This procedure allowed the neutral anabolics (testosterone, trenbolone and progesterone) to be isolated and separated from the acidic type (phenolic group), such as diethylstilbestrol, oestradiol, zeranol/zearalenone and their respective metabolites. The determination was effected using high-performance liquid chromatography with different detectors (ultraviolet, fluorimetric and electrochemical). Several analytical parameters were studied: chromatographic conditions, recoveries, evaporation step, solvent flow-rate, cartridges reusability, interference of plastic cartridges. For all the anabolics investigated the recoveries were greater than 83.6%.

Feature extraction and classification in automatic weld seam radioscopy

International Nuclear Information System (INIS)

Heindoerfer, F.; Pohle, R.

1994-01-01

The investigations conducted have shown that automatic feature extraction and classification procedures permit the identification of weld seam flaws. Within this context the favored learning fuzzy classificator represents a very good alternative to conventional classificators. The results have also made clear that improvements mainly in the field of image registration are still possible by increasing the resolution of the radioscopy system. Since, only if the flaw is segmented correctly, i.e. in its full size, and due to improved detail recognizability and sufficient contrast difference will an almost error-free classification be conceivable. (orig./MM) [de

A Raman spectroscopy bio-sensor for tissue discrimination in surgical robotics.

Science.gov (United States)

Ashok, Praveen C; Giardini, Mario E; Dholakia, Kishan; Sibbett, Wilson

2014-01-01

We report the development of a fiber-based Raman sensor to be used in tumour margin identification during endoluminal robotic surgery. Although this is a generic platform, the sensor we describe was adapted for the ARAKNES (Array of Robots Augmenting the KiNematics of Endoluminal Surgery) robotic platform. On such a platform, the Raman sensor is intended to identify ambiguous tissue margins during robot-assisted surgeries. To maintain sterility of the probe during surgical intervention, a disposable sleeve was specially designed. A straightforward user-compatible interface was implemented where a supervised multivariate classification algorithm was used to classify different tissue types based on specific Raman fingerprints so that it could be used without prior knowledge of spectroscopic data analysis. The protocol avoids inter-patient variability in data and the sensor system is not restricted for use in the classification of a particular tissue type. Representative tissue classification assessments were performed using this system on excised tissue. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Object-based Classification for Detecting Landslides and Stochastic Procedure to landslide susceptibility maps - A Case at Baolai Village, SW Taiwan

Science.gov (United States)

Lin, Ying-Tong; Chang, Kuo-Chen; Yang, Ci-Jian

2017-04-01

As the result of global warming in the past decades, Taiwan has experienced more and more extreme typhoons with hazardous massive landslides. In this study, we use object-oriented analysis method to classify landslide area at Baolai village by using Formosat-2 satellite images. We used for multiresolution segmented to generate the blocks, and used hierarchical logic to classified 5 different kinds of features. After that, classification the landslide into different type of landslide. Beside, we use stochastic procedure to integrate landslide susceptibility maps. This study assumed that in the extreme event, 2009 Typhoon Morakot, which precipitation goes to 1991.5mm in 5 days, and the highest landslide susceptible area. The results show that study area's landslide area was greatly changes, most of landslide was erosion by gully and made dip slope slide, or erosion by the stream, especially at undercut bank. From the landslide susceptibility maps, we know that the old landslide area have high potential to occur landslides in the extreme event. This study demonstrates the changing of landslide area and the landslide susceptible area. Keywords: Formosat-2, object-oriented, segmentation, classification, landslide, Baolai Village, SW Taiwan, FS

Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes

KAUST Repository

Cannistraci, Carlo

2010-09-01

Motivation: Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. Methods: \\'Minimum Curvilinearity\\' (MC) is a principle that-for small datasets-suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Results: Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. Conclusion: MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. © The Author(s) 2010. Published by Oxford University Press.

Weakly supervised classification in high energy physics

Energy Technology Data Exchange (ETDEWEB)

Dery, Lucio Mwinmaarong [Physics Department, Stanford University,Stanford, CA, 94305 (United States); Nachman, Benjamin [Physics Division, Lawrence Berkeley National Laboratory,1 Cyclotron Rd, Berkeley, CA, 94720 (United States); Rubbo, Francesco; Schwartzman, Ariel [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA, 94025 (United States)

2017-05-29

As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations. This paper presents a new approach called weakly supervised classification in which class proportions are the only input into the machine learning algorithm. Using one of the most challenging binary classification tasks in high energy physics — quark versus gluon tagging — we show that weakly supervised classification can match the performance of fully supervised algorithms. Furthermore, by design, the new algorithm is insensitive to any mis-modeling of discriminating features in the data by the simulation. Weakly supervised classification is a general procedure that can be applied to a wide variety of learning problems to boost performance and robustness when detailed simulations are not reliable or not available.

Weakly supervised classification in high energy physics

International Nuclear Information System (INIS)

Dery, Lucio Mwinmaarong; Nachman, Benjamin; Rubbo, Francesco; Schwartzman, Ariel

2017-01-01

As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations. This paper presents a new approach called weakly supervised classification in which class proportions are the only input into the machine learning algorithm. Using one of the most challenging binary classification tasks in high energy physics — quark versus gluon tagging — we show that weakly supervised classification can match the performance of fully supervised algorithms. Furthermore, by design, the new algorithm is insensitive to any mis-modeling of discriminating features in the data by the simulation. Weakly supervised classification is a general procedure that can be applied to a wide variety of learning problems to boost performance and robustness when detailed simulations are not reliable or not available.

Are joint and soft tissue injections painful? Results of a national French cross-sectional study of procedural pain in rheumatological practice

Directory of Open Access Journals (Sweden)

Poncet Coralie

2010-01-01

Full Text Available Abstract Background Joint, spinal and soft tissue injections are commonly performed by rheumatologists in their daily practice. Contrary to other procedures, e.g. performed in pediatric care, little is known about the frequency, the intensity and the management of procedural pain observed in osteo-articular injections in daily practice. Methods This observational, prospective, national study was carried out among a French national representative database of primary rheumatologists to evaluate the prevalence and intensity of pain caused by intra-and peri-articular injections, synovial fluid aspirations, soft tissue injections, and spinal injections. For each physician, data were collected over 1 month, for up to 40 consecutive patients (>18-years-old for whom a synovial fluid aspiration, an intra or peri-articular injection or a spinal injection were carried out during consultations. Statistical analysis was carried out in order to compare patients who had suffered from pain whilst undergoing the procedure to those who had not. Explanatory analyses were conducted by stepwise logistic regression with the characteristics of the patients to explain the existence of pain. Results Data were analysed for 8446 patients (64% female, mean age 62 ± 14 years recruited by 240 physicians. The predominant sites injected were the knee (45.5% and spine (19.1%. Over 80% of patients experienced procedural pain which was most common in the small joints (42% and spine (32% Pain was severe in 5.3% of patients, moderate in 26.6%, mild in 49.8%, and absent in 18.3%. Pain was significantly more intense in patients with severe pain linked to their underlying pathology and for procedures performed in small joints. Preventative or post-procedure analgesia was rarely given, only to 5.7% and 36.3% of patients, respectively. Preventative analgesia was more frequently prescribed in patients with more severe procedural pain. Conclusion Most patients undergoing intra-or peri

Classification of quantitative light-induced fluorescence images using convolutional neural network

NARCIS (Netherlands)

Imangaliyev, S.; van der Veen, M.H.; Volgenant, C.M.C.; Loos, B.G.; Keijser, B.J.F.; Crielaard, W.; Levin, E.; Lintas, A.; Rovetta, S.; Verschure, P.F.M.J.; Villa, A.E.P.

2017-01-01

Images are an important data source for diagnosis of oral diseases. The manual classification of images may lead to suboptimal treatment procedures due to subjective errors. In this paper an image classification algorithm based on Deep Learning framework is applied to Quantitative Light-induced

Automotive System for Remote Surface Classification.

Science.gov (United States)

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-04-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

Three-dimensional CT imaging of soft-tissue anatomy

International Nuclear Information System (INIS)

Fishman, E.K.; Ney, D.R.; Magid, D.; Kuhlman, J.E.

1988-01-01

Three-dimensional display of computed tomographic data has been limited to skeletal structures. This was in part related to the reconstruction algorithm used, which relied on a binary classification scheme. A new algorithm, volumetric rendering with percentage classification, provides the ability to display three-dimensional images of muscle and soft tissue. A review was conducted of images in 35 cases in which muscle and/or soft tissue were part of the clinical problem. In all cases, individual muscle groups could be clearly identified and discriminated. Branching vessels in the range of 2.3 mm could be identified. Similarly, lymph nodes could be clearly defined. High-resolution three-dimensional images were found to be useful both in providing an increased understanding of complex muscle and soft tissue anatomy and in surgical planning

Exploring different approaches for music genre classification

Directory of Open Access Journals (Sweden)

Antonio Jose Homsi Goulart

2012-07-01

Full Text Available In this letter, we present different approaches for music genre classification. The proposed techniques, which are composed of a feature extraction stage followed by a classification procedure, explore both the variations of parameters used as input and the classifier architecture. Tests were carried out with three styles of music, namely blues, classical, and lounge, which are considered informally by some musicians as being “big dividers” among music genres, showing the efficacy of the proposed algorithms and establishing a relationship between the relevance of each set of parameters for each music style and each classifier. In contrast to other works, entropies and fractal dimensions are the features adopted for the classifications.

The Application of Tissue Engineering Procedures to Repair the Larynx

Science.gov (United States)

Ringel, Robert L.; Kahane, Joel C.; Hillsamer, Peter J.; Lee, Annie S.; Badylak, Stephen F.

2006-01-01

The field of tissue engineering/regenerative medicine combines the quantitative principles of engineering with the principles of the life sciences toward the goal of reconstituting structurally and functionally normal tissues and organs. There has been relatively little application of tissue engineering efforts toward the organs of speech, voice,…

The development of rock suitability classification strategies in the Finnish spent nuclear fuel disposal program

International Nuclear Information System (INIS)

Hellae, Pirjo; Hagros, Annika; Aaltonen, Ismo; Kosunen, Paula; Mattila, Jussi

2015-01-01

This paper describes the development of the rock suitability classification strategies applied to locate the spent fuel repository in crystalline rock in Finland. Development of the classification procedure is motivated not only by the regulatory requirements, but also by the need to more closely integrate site characterization, repository design and long-term safety assessment. The classification procedure has been developed along with the increasing level of detail of the available site data and knowledge on the performance of the engineered barrier system (EBS). The classification system has also been adapted to the changes in the regulations. The present form of the classification system and experiences from testing the system at the site are described. Demonstration activities have shown that the criteria and the stepwise research, construction and decision making protocol can be applied successfully.

The development of rock suitability classification strategies in the Finnish spent nuclear fuel disposal program

Energy Technology Data Exchange (ETDEWEB)

Hellae, Pirjo; Hagros, Annika [Saanio and Riekkola Oy (Finland); Aaltonen, Ismo; Kosunen, Paula; Mattila, Jussi [Posiva Oy (Finland)

2015-07-01

This paper describes the development of the rock suitability classification strategies applied to locate the spent fuel repository in crystalline rock in Finland. Development of the classification procedure is motivated not only by the regulatory requirements, but also by the need to more closely integrate site characterization, repository design and long-term safety assessment. The classification procedure has been developed along with the increasing level of detail of the available site data and knowledge on the performance of the engineered barrier system (EBS). The classification system has also been adapted to the changes in the regulations. The present form of the classification system and experiences from testing the system at the site are described. Demonstration activities have shown that the criteria and the stepwise research, construction and decision making protocol can be applied successfully.

An algorithm for the arithmetic classification of multilattices.

Science.gov (United States)

Indelicato, Giuliana

2013-01-01

A procedure for the construction and the classification of monoatomic multilattices in arbitrary dimension is developed. The algorithm allows one to determine the location of the points of all monoatomic multilattices with a given symmetry, or to determine whether two assigned multilattices are arithmetically equivalent. This approach is based on ideas from integral matrix theory, in particular the reduction to the Smith normal form, and can be coded to provide a classification software package.

Integrated tracking, classification, and sensor management theory and applications

CERN Document Server

Krishnamurthy, Vikram; Vo, Ba-Ngu

2012-01-01

A unique guide to the state of the art of tracking, classification, and sensor management. This book addresses the tremendous progress made over the last few decades in algorithm development and mathematical analysis for filtering, multi-target multi-sensor tracking, sensor management and control, and target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical formulation, clear description of the theory, and real-world applications. Written by experts in the field, Integrated Tracking, Classification, and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multi-target tracking approaches, target classification procedures, and large scale sensor management problem-solving techniques.

Relationship between opioid therapy, tissue-damaging procedures, and brain metabolites as measured by proton MRS in asphyxiated term neonates.

Science.gov (United States)

Angeles, Danilyn M; Ashwal, Stephen; Wycliffe, Nathaniel D; Ebner, Charlotte; Fayard, Elba; Sowers, Lawrence; Holshouser, Barbara A

2007-05-01

To examine the effects of opioid and tissue-damaging procedures (TDPs) [i.e. procedures performed in the neonatal intensive care unit (NICU) known to result in pain, stress, and tissue damage] on brain metabolites, we reviewed the medical records of 28 asphyxiated term neonates (eight opioid-treated, 20 non-opioid treated) who had undergone magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (MRS) within the first month of life as well as eight newborns with no clinical findings of asphyxial injury. We found that lower creatine (Cr), myoinositol (Ins), and N-acetylaspartate (NAA)/choline (Cho) (p OGM) NAA/Cr was decreased (p = 0.03) and lactate (Lac) was present in a significantly higher amount (40%; p = 0.03) in non-opioid-treated neonates compared with opioid-treated neonates. Compared with controls, untreated neonates showed larger changes in more metabolites in basal ganglia (BG), thalami (TH), and OGM with greater significance than treated neonates. Our data suggest that TDPs affect spectral metabolites and that opioids do not cause harm in asphyxiated term neonates exposed to repetitive TDPs in the first 2-4 DOL and may provide a degree of neuroprotection.

Pancreatic neuroendocrine tumours: correlation between MSCT features and pathological classification

Energy Technology Data Exchange (ETDEWEB)

Luo, Yanji; Dong, Zhi; Li, Zi-Ping; Feng, Shi-Ting [The First Affiliated Hospital, Sun Yat-Sen University, Department of Radiology, Guangzhou, Guangdong (China); Chen, Jie [The First Affiliated Hospital, Sun Yat-Sen University, Department of Gastroenterology, Guangzhou, Guangdong (China); Chan, Tao; Chen, Minhu [Union Hospital, Hong Kong, Medical Imaging Department, Shatin, N.T. (China); Lin, Yuan [The First Affiliated Hospital, Sun Yat-Sen University, Department of Pathology, Guangzhou, Guangdong (China)

2014-11-15

We aimed to evaluate the multi-slice computed tomography (MSCT) features of pancreatic neuroendocrine neoplasms (P-NENs) and analyse the correlation between the MSCT features and pathological classification of P-NENs. Forty-one patients, preoperatively investigated by MSCT and subsequently operated on with a histological diagnosis of P-NENs, were included. Various MSCT features of the primary tumour, lymph node, and distant metastasis were analysed. The relationship between MSCT features and pathologic classification of P-NENs was analysed with univariate and multivariate models. Contrast-enhanced images showed significant differences among the three grades of tumours in the absolute enhancement (P = 0.013) and relative enhancement (P = 0.025) at the arterial phase. Univariate analysis revealed statistically significant differences among the tumours of different grades (based on World Health Organization [WHO] 2010 classification) in tumour size (P = 0.001), tumour contour (P < 0.001), cystic necrosis (P = 0.001), tumour boundary (P = 0.003), dilatation of the main pancreatic duct (P = 0.001), peripancreatic tissue or vascular invasion (P < 0.001), lymphadenopathy (P = 0.011), and distant metastasis (P = 0.012). Multivariate analysis suggested that only peripancreatic tissue or vascular invasion (HR 3.934, 95 % CI, 0.426-7.442, P = 0.028) was significantly associated with WHO 2010 pathological classification. MSCT is helpful in evaluating the pathological classification of P-NENs. (orig.)

Behavioral state classification in epileptic brain using intracranial electrophysiology

Science.gov (United States)

Kremen, Vaclav; Duque, Juliano J.; Brinkmann, Benjamin H.; Berry, Brent M.; Kucewicz, Michal T.; Khadjevand, Fatemeh; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Worrell, Gregory A.

2017-04-01

Objective. Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach. Data from seven patients (age 34+/- 12 , 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1-600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results. Classification accuracy of 97.8  ±  0.3% (normal tissue) and 89.4  ±  0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8  ±  0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1  ±  1.6%). Spectral power in high frequency band features (Ripple (80-250 Hz), Fast Ripple (250-600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy  ⩾90% using a single electrode contact and single spectral feature. Significance. Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.

On the introduction of secondary fingerprint classification

CSIR Research Space (South Africa)

Msiza, IS

2011-07-01

Full Text Available The concept of fingerprint classification is an important one because of the need to, before executing a database search procedure, virtually break the fingerprint template database into smaller, manageable partitions. This is done in order to avoid...

Safety classification of nuclear power plant systems, structures and components

International Nuclear Information System (INIS)

1992-01-01

The Safety Classification principles used for the systems, structures and components of a nuclear power plant are detailed in the guide. For classification, the nuclear power plant is divided into structural and operational units called systems. Every structure and component under control is included into some system. The Safety Classes are 1, 2 and 3 and the Class EYT (non-nuclear). Instructions how to assign each system, structure and component to an appropriate safety class are given in the guide. The guide applies to new nuclear power plants and to the safety classification of systems, structures and components designed for the refitting of old nuclear power plants. The classification principles and procedures applying to the classification document are also given

Visualization of Nonlinear Classification Models in Neuroimaging - Signed Sensitivity Maps

DEFF Research Database (Denmark)

Rasmussen, Peter Mondrup; Schmah, Tanya; Madsen, Kristoffer Hougaard

2012-01-01

Classification models are becoming increasing popular tools in the analysis of neuroimaging data sets. Besides obtaining good prediction accuracy, a competing goal is to interpret how the classifier works. From a neuroscientific perspective, we are interested in the brain pattern reflecting...... the underlying neural encoding of an experiment defining multiple brain states. In this relation there is a great desire for the researcher to generate brain maps, that highlight brain locations of importance to the classifiers decisions. Based on sensitivity analysis, we develop further procedures for model...... direction the individual locations influence the classification. We illustrate the visualization procedure on a real data from a simple functional magnetic resonance imaging experiment....

Transcriptome classification reveals molecular subtypes in psoriasis

Directory of Open Access Journals (Sweden)

Ainali Chrysanthi

2012-09-01

Full Text Available Abstract Background Psoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation. Although certain clinical phenotypes, such as plaque psoriasis, are well defined, it is currently unclear whether there are molecular subtypes that might impact on prognosis or treatment outcomes. Results We present a pipeline for patient stratification through a comprehensive analysis of gene expression in paired lesional and non-lesional psoriatic tissue samples, compared with controls, to establish differences in RNA expression patterns across all tissue types. Ensembles of decision tree predictors were employed to cluster psoriatic samples on the basis of gene expression patterns and reveal gene expression signatures that best discriminate molecular disease subtypes. This multi-stage procedure was applied to several published psoriasis studies and a comparison of gene expression patterns across datasets was performed. Conclusion Overall, classification of psoriasis gene expression patterns revealed distinct molecular sub-groups within the clinical phenotype of plaque psoriasis. Enrichment for TGFb and ErbB signaling pathways, noted in one of the two psoriasis subgroups, suggested that this group may be more amenable to therapies targeting these pathways. Our study highlights the potential biological relevance of using ensemble decision tree predictors to determine molecular disease subtypes, in what may initially appear to be a homogenous clinical group. The R code used in this paper is available upon request.

Involvement of Machine Learning for Breast Cancer Image Classification: A Survey.

Science.gov (United States)

Nahid, Abdullah-Al; Kong, Yinan

2017-01-01

Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

Directory of Open Access Journals (Sweden)

Abdullah-Al Nahid

2017-01-01

Full Text Available Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN, Logic Based classifiers such as the Random Forest (RF algorithm, Support Vector Machines (SVM, Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

Hybrid classification: the case of the acquisition procedure documentation within and ouside the Public Contracts information systems in Alto Adige Region

Directory of Open Access Journals (Sweden)

Francesca Delneri

2017-05-01

Full Text Available With reference to the acquisition procedures, the related documentation is created and managed mostly on the platform of the subcontracting institution, partly on the Alto Adige Public Sector Contracts information system. With a partial integration between this system and the platform made available by the Agenzia per i procedimenti e la vigilanza in materia di contratti pubblici di lavori, servizi e forniture, classification and filing information can be assigned to the documents coming from both platform, while the reunification of documents related to the same process is transferred to the preservation system as unique archive of the administration.

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

Clinical considerations for regenerative endodontic procedures.

Science.gov (United States)

Geisler, Todd M

2012-07-01

The management of a tooth with incomplete root maturation and a necrotic pulp is an endodontic and a restorative challenge. Apexification procedures alone leave the tooth in a weakened state and at risk for reinfection. Regenerative endodontic procedures potentially offer advantages, including the possibility of hard tissue deposition and continued root development. Case studies have reported regeneration of human pulplike tissues in vivo, but there is no protocol that reliably regenerates pulplike tissue. This article summarizes historical, current, and future regenerative treatment approaches. Copyright © 2012 Elsevier Inc. All rights reserved.

Soft tissue recurrence of giant cell tumor of the bone: Prevalence and radiographic features

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Leilei Xu

2017-11-01

Full Text Available Aim: Recurrence of giant cell tumor of bone (GCTB in the soft tissue is rarely seen in the clinical practice. This study aims to determine the prevalence of soft tissue recurrence of GCTB, and to characterize its radiographic features. Methods: A total of 291 patients treated by intralesional curettage for histologically diagnosed GCTB were reviewed. 6 patients were identified to have the recurrence of GCTB in the soft tissue, all of whom had undergone marginal resection of the lesion. Based on the x-ray, CT and MRI imaging, the radiographic features of soft tissue recurrence were classified into 3 types. Type I was defined as soft tissue recurrence with peripheral ossification, type II was defined as soft tissue recurrence with central ossification, and type III was defined as pure soft tissue recurrence without ossification. Demographic data including period of recurrence and follow-up duration after the second surgery were recorded for these 6 patients. Musculoskeletal Tumor Society (MSTS scoring system was used to evaluate functional outcomes. Results: The overall recurrence rate was 2.1% (6/291. The mean interval between initial surgery and recurrence was 11.3 ± 4.1 months (range, 5–17. The recurrence lesions were located in the thigh of 2 patients, in the forearm of 2 patients and in the leg of the other 2 patients. According to the classification system mentioned above, 2 patients were classified with type I, 1 as type II and 3 as type III. After the marginal excision surgery, all patients were consistently followed up for a mean period of 13.4 ± 5.3 months (range, 6–19, with no recurrence observed at the final visit. All the patients were satisfied with the surgical outcome. According to the MSTS scale, the mean postoperative functional score was 28.0 ± 1.2 (range, 26–29. Conclusions: The classification of soft tissue recurrence of GCTB may be helpful for the surgeon to select the appropriate imaging procedure to

A single simple procedure for dewaxing, hydration and heat-induced epitope retrieval (HIER for immunohistochemistry in formalin fixed paraffin-embedded tissue

Directory of Open Access Journals (Sweden)

I.M.S. Paulsen

2015-11-01

Full Text Available Heat-induced epitope retrieval (HIER is widely used for immunohistochemistry on formalin fixed paraffin-embedded tissue and includes temperatures well above the melting point of paraffin. We therefore tested whether traditional xylene-based removal of paraffin is required on sections from paraffin-embedded tissue, when HIER is performed by vigorous boiling in 10 mM Tris/0.5 mM EGTA-buffer (pH=9. Immunohistochemical results using HIER with or without prior dewaxing in xylene were evaluated using 7 primary antibodies targeting proteins located in the cytosol, intracellular vesicles and plasma membrane. No effect of omitting prior dewaxing was observed on staining pattern. Semiquantitative analysis did not show HIER to influence the intensity of labelling consistently. Consequently, quantification of immune labelling intensity using fluorescent secondary antibodies was performed at 5 dilutions of primary antibody with and without prior dewaxing in xylene. No effect of omitting prior dewaxing on signal intensity was detectable indicating similar immunoreactivity in dewaxed and non-dewaxed sections. The intensity of staining the nucleus with the DNA-stain ToPro3 was similarly unaffected by omission of dewaxing in xylene. In conclusion, the HIER procedure described and tested can be used as a single procedure enabling dewaxing, hydration and epitope retrieval for immunohistochemistry in formalin fixed paraffin-embedded tissue.

Procedural pain in neonatal units in Kenya.

Science.gov (United States)

Kyololo, O'Brien Munyao; Stevens, Bonnie; Gastaldo, Denise; Gisore, Peter

2014-11-01

To determine the nature and frequency of painful procedures and procedural pain management practices in neonatal units in Kenya. Cross-sectional survey. Level I and level II neonatal units in Kenya. Ninety-five term and preterm neonates from seven neonatal units. Medical records of neonates admitted for at least 24 h were reviewed to determine the nature and frequency of painful procedures performed in the 24 h period preceding data collection (6:00 to 6:00) as well as the pain management interventions (eg, morphine, breastfeeding, skin-to-skin contact, containment, non-nutritive sucking) that accompanied each procedure. Neonates experienced a total of 404 painful procedures over a 24 h period (mean=4.3, SD 2.0; range 1-12); 270 tissue-damaging (mean=2.85, SD 1.1; range 1-6) and 134 non-tissue-damaging procedures (mean=1.41, SD 1.2; range 0-6). Peripheral cannula insertion (27%) and intramuscular injections (22%) were the most common painful procedures. Ventilated neonates and neonates admitted in level II neonatal units had a higher number of painful procedures than those admitted in level I units (mean 4.76 vs 2.96). Only one procedure had a pain intensity score documented; and none had been performed with any form of analgesia. Neonates in Kenya were exposed to numerous tissue-damaging and non-tissue-damaging procedures without any form of analgesia. Our findings suggest that education is needed on how to assess and manage procedural pain in neonatal units in Kenya. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Fuzzy logic algorithm for quantitative tissue characterization of diffuse liver diseases from ultrasound images.

Science.gov (United States)

Badawi, A M; Derbala, A S; Youssef, A M

1999-08-01

Computerized ultrasound tissue characterization has become an objective means for diagnosis of liver diseases. It is difficult to differentiate diffuse liver diseases, namely cirrhotic and fatty liver by visual inspection from the ultrasound images. The visual criteria for differentiating diffused diseases are rather confusing and highly dependent upon the sonographer's experience. This often causes a bias effects in the diagnostic procedure and limits its objectivity and reproducibility. Computerized tissue characterization to assist quantitatively the sonographer for the accurate differentiation and to minimize the degree of risk is thus justified. Fuzzy logic has emerged as one of the most active area in classification. In this paper, we present an approach that employs Fuzzy reasoning techniques to automatically differentiate diffuse liver diseases using numerical quantitative features measured from the ultrasound images. Fuzzy rules were generated from over 140 cases consisting of normal, fatty, and cirrhotic livers. The input to the fuzzy system is an eight dimensional vector of feature values: the mean gray level (MGL), the percentile 10%, the contrast (CON), the angular second moment (ASM), the entropy (ENT), the correlation (COR), the attenuation (ATTEN) and the speckle separation. The output of the fuzzy system is one of the three categories: cirrhosis, fatty or normal. The steps done for differentiating the pathologies are data acquisition and feature extraction, dividing the input spaces of the measured quantitative data into fuzzy sets. Based on the expert knowledge, the fuzzy rules are generated and applied using the fuzzy inference procedures to determine the pathology. Different membership functions are developed for the input spaces. This approach has resulted in very good sensitivities and specificity for classifying diffused liver pathologies. This classification technique can be used in the diagnostic process, together with the history

Adipose tissue-derived mesenchymal stem cell yield and growth characteristics are affected by the tissue-harvesting procedure

NARCIS (Netherlands)

Oedayrajsingh-Varma, M. J.; van Ham, S. M.; Knippenberg, M.; Helder, M. N.; Klein-Nulend, J.; Schouten, T. E.; Ritt, M. J. P. F.; van Milligen, F. J.

2006-01-01

Adipose tissue contains a stromal vascular fraction that can be easily isolated and provides a rich source of adipose tissue-derived mesenchymal stem cells (ASC). These ASC are a potential source of cells for tissue engineering. We studied whether the yield and growth characteristics of ASC were

Random forests for classification in ecology

Science.gov (United States)

Cutler, D.R.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J.

2007-01-01

Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature. ?? 2007 by the Ecological Society of America.

"In situ preparation": new surgical procedure indicated for soft-tissue sarcoma of a lower limb in close proximity to major neurovascular structures.

Science.gov (United States)

Matsumoto, Seiichi; Kawaguchi, Noriyoshi; Manabe, Jun; Matsushita, Yasushi

2002-02-01

When soft-tissue sarcomas occur near neurovascular structures, preoperative images cannot always reveal the accurate relationship between the tumor and these structures. Therefore, in some patients, neurovascular structures are sacrificed unnecessarily. In other patients, neurovascular structures are preserved with an inappropriate margin, followed by local recurrence. The objective of this study was to evaluate a new surgical method, "in situ preparation" (ISP), which enables the preparation of neurovascular bundles and the intraoperative evaluation of the surgical margin without contamination by tumor cells. With this method, additional procedures, including pasteurization, alcohol soaking, and distilled water soaking of the preserved neurovascular bundle can also be performed to preserve the continuity of vessels. Between April 1992 and December 1998, 18 patients with soft-tissue sarcoma were operated on using ISP. The tumor and neurovascular structure were lifted en bloc from the surgical bed and separated from the field by the use of a vinyl sheet. The consistency of the neurovascular structures was preserved. The tissue block could be freely turned around and the neurovascular structure was separated from the block through the nearest approach. The margin between the tumor and neurovascular structure was evaluated, and an additional procedure, such as pasteurization, alcohol soaking or distilled water soaking, was performed, according to the safety of the surgical margin. Only one patient showed recurrence after ISP. Complications after ISP were arterial occlusion in two patients and nerve palsy in three patients. The main cause of these complications was the long period of pasteurization; modified additional procedures could prevent such complications. ISP is a useful method with which to ensure a safe surgical margin and good functional results.

Phonosurgery of the vocal folds : a classification proposal

NARCIS (Netherlands)

Remacle, M; Friedrich, G; Dikkers, FG; de Jong, F

The Phonosurgery Committee of the European Laryngological Society (ELS) has examined the definition and technical description of phonosurgical procedures. Based on this review, the committee has proposed a working classification. The current presentation is restricted to vocal fold surgery (VFS)

The impact of laser ablation on optical soft tissue differentiation for tissue specific laser surgery-an experimental ex vivo study

Directory of Open Access Journals (Sweden)

Stelzle Florian

2012-06-01

Full Text Available Abstract Background Optical diffuse reflectance can remotely differentiate various bio tissues. To implement this technique in an optical feedback system to guide laser surgery in a tissue-specific way, the alteration of optical tissue properties by laser ablation has to be taken into account. It was the aim of this study to evaluate the general feasibility of optical soft tissue differentiation by diffuse reflectance spectroscopy under the influence of laser ablation, comparing the tissue differentiation results before and after laser intervention. Methods A total of 70 ex vivo tissue samples (5 tissue types were taken from 14 bisected pig heads. Diffuse reflectance spectra were recorded before and after Er:YAG-laser ablation. The spectra were analyzed and differentiated using principal component analysis (PCA, followed by linear discriminant analysis (LDA. To assess the potential of tissue differentiation, area under the curve (AUC, sensitivity and specificity was computed for each pair of tissue types before and after laser ablation, and compared to each other. Results Optical tissue differentiation showed good results before laser exposure (total classification error 13.51%. However, the tissue pair nerve and fat yielded lower AUC results of only 0.75. After laser ablation slightly reduced differentiation results were found with a total classification error of 16.83%. The tissue pair nerve and fat showed enhanced differentiation (AUC: 0.85. Laser ablation reduced the sensitivity in 50% and specificity in 80% of the cases of tissue pair comparison. The sensitivity of nerve–fat differentiation was enhanced by 35%. Conclusions The observed results show the general feasibility of tissue differentiation by diffuse reflectance spectroscopy even under conditions of tissue alteration by laser ablation. The contrast enhancement for the differentiation between nerve and fat tissue after ablation is assumed to be due to laser removal of the

Neural tissue-spheres

DEFF Research Database (Denmark)

Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

2007-01-01

By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

Current concepts in non-gastrointestinal stromal tumor soft tissue sarcomas: A primer for radiologists

Energy Technology Data Exchange (ETDEWEB)

Baheti, Akahay D. [Dept. of Radiology, Tata Memorial Centre, Mumbai (India); Tirumani, Harika [Dept. of Radiology, University of Arkansas for Medical Sciences, Little Rock (United States); O' Neill, Alibhe; Jagannathan, Jyothi P. [Dept. of Imaging, Dana-Farber Cancer Institute, Boston (United States)

2017-01-15

Non-gastrointestinal stromal tumor (GIST) soft tissue sarcomas (STSs) are a heterogeneous group of neoplasms whose classification and management continues to evolve with better understanding of their biologic behavior. The 2013 World Health Organization (WHO) has revised their classification based on new immunohistochemical and cytogenetic data. In this article, we will provide a brief overview of the revised WHO classification of soft tissue tumors, discuss in detail the radiology and management of the two most common adult non-GIST STS, namely liposarcoma and leiomyosarcoma, and review some of the emerging histology-driven targeted therapies in non-GIST STS, focusing on the role of the radiologist.

Current concepts in non-gastrointestinal stromal tumor soft tissue sarcomas: A primer for radiologists

International Nuclear Information System (INIS)

Baheti, Akahay D.; Tirumani, Harika; O'Neill, Alibhe; Jagannathan, Jyothi P.

2017-01-01

Non-gastrointestinal stromal tumor (GIST) soft tissue sarcomas (STSs) are a heterogeneous group of neoplasms whose classification and management continues to evolve with better understanding of their biologic behavior. The 2013 World Health Organization (WHO) has revised their classification based on new immunohistochemical and cytogenetic data. In this article, we will provide a brief overview of the revised WHO classification of soft tissue tumors, discuss in detail the radiology and management of the two most common adult non-GIST STS, namely liposarcoma and leiomyosarcoma, and review some of the emerging histology-driven targeted therapies in non-GIST STS, focusing on the role of the radiologist

A neural network for noise correlation classification

Science.gov (United States)

Paitz, Patrick; Gokhberg, Alexey; Fichtner, Andreas

2018-02-01

We present an artificial neural network (ANN) for the classification of ambient seismic noise correlations into two categories, suitable and unsuitable for noise tomography. By using only a small manually classified data subset for network training, the ANN allows us to classify large data volumes with low human effort and to encode the valuable subjective experience of data analysts that cannot be captured by a deterministic algorithm. Based on a new feature extraction procedure that exploits the wavelet-like nature of seismic time-series, we efficiently reduce the dimensionality of noise correlation data, still keeping relevant features needed for automated classification. Using global- and regional-scale data sets, we show that classification errors of 20 per cent or less can be achieved when the network training is performed with as little as 3.5 per cent and 16 per cent of the data sets, respectively. Furthermore, the ANN trained on the regional data can be applied to the global data, and vice versa, without a significant increase of the classification error. An experiment where four students manually classified the data, revealed that the classification error they would assign to each other is substantially larger than the classification error of the ANN (>35 per cent). This indicates that reproducibility would be hampered more by human subjectivity than by imperfections of the ANN.

A semi-automated measuring system of brain diffusion and perfusion magnetic resonance imaging abnormalities in patients with multiple sclerosis based on the integration of coregistration and tissue segmentation procedures

International Nuclear Information System (INIS)

Revenaz, Alfredo; Ruggeri, Massimiliano; Laganà, Marcella; Bergsland, Niels; Groppo, Elisabetta; Rovaris, Marco; Fainardi, Enrico

2016-01-01

Diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) abnormalities in patients with multiple sclerosis (MS) are currently measured by a complex combination of separate procedures. Therefore, the purpose of this study was to provide a reliable method for reducing analysis complexity and obtaining reproducible results. We implemented a semi-automated measuring system in which different well-known software components for magnetic resonance imaging (MRI) analysis are integrated to obtain reliable measurements of DWI and PWI disturbances in MS. We generated the Diffusion/Perfusion Project (DPP) Suite, in which a series of external software programs are managed and harmonically and hierarchically incorporated by in-house developed Matlab software to perform the following processes: 1) image pre-processing, including imaging data anonymization and conversion from DICOM to Nifti format; 2) co-registration of 2D and 3D non-enhanced and Gd-enhanced T1-weighted images in fluid-attenuated inversion recovery (FLAIR) space; 3) lesion segmentation and classification, in which FLAIR lesions are at first segmented and then categorized according to their presumed evolution; 4) co-registration of segmented FLAIR lesion in T1 space to obtain the FLAIR lesion mask in the T1 space; 5) normal appearing tissue segmentation, in which T1 lesion mask is used to segment basal ganglia/thalami, normal appearing grey matter (NAGM) and normal appearing white matter (NAWM); 6) DWI and PWI map generation; 7) co-registration of basal ganglia/thalami, NAGM, NAWM, DWI and PWI maps in previously segmented FLAIR space; 8) data analysis. All these steps are automatic, except for lesion segmentation and classification. We developed a promising method to limit misclassifications and user errors, providing clinical researchers with a practical and reproducible tool to measure DWI and PWI changes in MS

Classification and regression trees

CERN Document Server

Breiman, Leo; Olshen, Richard A; Stone, Charles J

1984-01-01

The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

Procedures for health risk assessment in Europe

NARCIS (Netherlands)

Seeley, M.R.; Tonner-Navarro, L.E.; Beck, B.D.; Deskin, R.; Feron, V.J.; Johanson, G.; Bolt, H.M.

2001-01-01

This report compares cancer classification systems, health risk assessment approaches, and procedures used for establishing occupational exposure limits (OELs), in various European countries and scientific organizations. The objectives were to highlight and compare key aspects of these processes and

Conformal radiotherapy: principles and classification

International Nuclear Information System (INIS)

Rosenwald, J.C.; Gaboriaud, G.; Pontvert, D.

1999-01-01

'Conformal radiotherapy' is the name fixed by usage and given to a new form of radiotherapy resulting from the technological improvements observed during the last ten years. While this terminology is now widely used, no precise definition can be found in the literature. Conformal radiotherapy refers to an approach in which the dose distribution is more closely 'conformed' or adapted to the actual shape of the target volume. However, the achievement of a consensus on a more specific definition is hampered by various difficulties, namely in characterizing the degree of 'conformality'. We have therefore suggested a classification scheme be established on the basis of the tools and the procedures actually used for all steps of the process, i.e., from prescription to treatment completion. Our classification consists of four levels: schematically, at level 0, there is no conformation (rectangular fields); at level 1, a simple conformation takes place, on the basis of conventional 2D imaging; at level 2, a 3D reconstruction of the structures is used for a more accurate conformation; and level 3 includes research and advanced dynamic techniques. We have used our personal experience, contacts with colleagues and data from the literature to analyze all the steps of the planning process, and to define the tools and procedures relevant to a given level. The corresponding tables have been discussed and approved at the European level within the Dynarad concerted action. It is proposed that the term 'conformal radiotherapy' be restricted to procedures where all steps are at least at level 2. (author)

Headache and endovascular procedures.

Science.gov (United States)

de Biase, Stefano; Longoni, Marco; Gigli, Gian Luigi; Agostoni, Elio

2017-05-01

The International Classification of Headache Disorders (ICHD-3 beta) includes headache attributed to intracranial endovascular procedures (EVPs). The aim of this review is to describe the clinical and pathophysiological aspects of headache related to vascular lesions and EVPs. Current studies regarding this issue are contradictory, although generally favouring headache improvement after EVPs. Further large studies are needed to adequately assess the effect of EVPs on headache.

Update and validation of the Society for Vascular Surgery wound, ischemia, and foot infection threatened limb classification system.

Science.gov (United States)

Mills, Joseph L

2014-03-01

The diagnosis of critical limb ischemia, first defined in 1982, was intended to delineate a patient cohort with a threatened limb and at risk for amputation due to severe peripheral arterial disease. The influence of diabetes and its associated neuropathy on the pathogenesis-threatened limb was an excluded comorbidity, despite its known contribution to amputation risk. The Fontaine and Rutherford classifications of limb ischemia severity have also been used to predict amputation risk and the likelihood of tissue healing. The dramatic increase in the prevalence of diabetes mellitus and the expanding techniques of arterial revascularization has prompted modification of peripheral arterial disease classification schemes to improve outcomes analysis for patients with threatened limbs. The diabetic patient with foot ulceration and infection is at risk for limb loss, with abnormal arterial perfusion as only one determinant of outcome. The wound extent and severity of infection also impact the likelihood of limb loss. To better predict amputation risk, the Society for Vascular Surgery Lower Extremity Guidelines Committee developed a classification of the threatened lower extremity that reflects these important clinical considerations. Risk stratification is based on three major factors that impact amputation risk and clinical management: wound, ischemia, and foot infection. This classification scheme is relevant to the patient with critical limb ischemia because many are also diabetic. Implementation of the wound, ischemia, and foot infection classification system in critical limb ischemia patients is recommended and should assist the clinician in more meaningful analysis of outcomes for various forms of wound and arterial revascularizations procedures required in this challenging, patient population. Copyright © 2014 Elsevier Inc. All rights reserved.

A statistical approach to root system classification.

Directory of Open Access Journals (Sweden)

Gernot eBodner

2013-08-01

Full Text Available Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for plant functional type identification in ecology can be applied to the classification of root systems. We demonstrate that combining principal component and cluster analysis yields a meaningful classification of rooting types based on morphological traits. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. Biplot inspection is used to determine key traits and to ensure stability in cluster based grouping. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Three rooting types emerged from measured data, distinguished by diameter/weight, density and spatial distribution respectively. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement

Neuromuscular disease classification system

Science.gov (United States)

Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

2013-06-01

Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

Anthropomorphic phantom materials

International Nuclear Information System (INIS)

White, D.R.; Constantinou, C.

1982-01-01

The need, terminology and history of tissue substitutes are outlined. Radiation properties of real tissues are described and simulation procedures are outlined. Recent tissue substitutes are described and charted, as are calculated radiation classifications. Manufacturing procedures and quality control are presented. Recent phantom studies are reviewed and a discussion recorded. Elemental compositions of the recommended tissue substitutes are charted with elemental composition given for each tissue substitute

Mass Spectrometry Imaging for the Classification of Tumor Tissue

NARCIS (Netherlands)

Mascini, N.E.

2016-01-01

Mass spectrometry imaging (MSI) can detect and identify many different molecules without the need for labeling. In addition, it can provide their spatial distributions as ‘molecular maps’. These features make MSI well suited for studying the molecular makeup of tumor tissue. Currently, there is an

Integration of emergency action levels with Combustion Engineering Emergency Operating Procedures

International Nuclear Information System (INIS)

Faletti, D.W.; Jamison, J.D.

1985-09-01

This report documents the development of a method for integrating Emergency Action Levels (EALs) with plant-specific Emergency Operating Procedures (EOPs) using the Combustion Engineering Owners' Group Emergency Operating Procedure Technical Guidelines (CEOG EOPTFs). EALs are discrete conditions or values of plant operating parameters which, if exceeded, require declaration of an appropriate level of emergency. At most operating plants, the EALs and event classification procedures are totally separate from the Emergency Operating Procedures used by the plant staff to control the plant during abnormal conditions. Control room personnel using the EOPs to deal with abnormal plant conditions must recognize when plant safety is sufficiently degraded that an emergency declaration may be warranted, and then enter a separate classification procedure containing EALs for a number of plant conditions and parameters. The operator then compares the existing plant conditions to the EALs and makes an emergency declaration accordingly. Using the Combustion Engineering Owners' Group Technical Guidelines document, a set of emergency class definitions and criteria were developed based on the status of the three main fission product barriers (fuel cladding, primary coolant system and containment). The EOPTGs were then annotated with suggested guidance to a procedure writer. The proposed method was tested by applying it to the reactor accident sequences that were shown in the reactor safety study to dominate accident risk. The object of the test was to determine if an EAL set linked to the EOP annotations would produce timely and accurate classification of the risk-dominant sequences. 6 refs., 13 figs., 31 tabs

Robust classification of traffic signs using multi-view cues

NARCIS (Netherlands)

Hazelhoff, L.; Creusen, I.M.; With, de P.H.N.

2012-01-01

Traffic sign inventories are created for road safety and maintenance based on street-level panoramic images. Due to the large capturing interval, large viewpoint deviations between the different capturings occur. These viewpoint variations complicate the classification procedure, which aims at the

The 2017 international classification of the Ehlers-Danlos syndromes

DEFF Research Database (Denmark)

Malfait, Fransiska; Francomano, Clair; Byers, Peter H

2017-01-01

The Ehlers-Danlos syndromes (EDS) are a clinically and genetically heterogeneous group of heritable connective tissue disorders (HCTDs) characterized by joint hypermobility, skin hyperextensibility, and tissue fragility. Over the past two decades, the Villefranche Nosology, which delineated six s...... that the revised International EDS Classification will serve as a new standard for the diagnosis of EDS and will provide a framework for future research purposes. © 2017 Wiley Periodicals, Inc......., and mutations have been identified in an array of novel genes. The International EDS Consortium proposes a revised EDS classification, which recognizes 13 subtypes. For each of the subtypes, we propose a set of clinical criteria that are suggestive for the diagnosis. However, in view of the vast genetic...... revised the clinical criteria for hypermobile EDS in order to allow for a better distinction from other joint hypermobility disorders. To satisfy research needs, we also propose a pathogenetic scheme, that regroups EDS subtypes for which the causative proteins function within the same pathway. We hope...

Scalable Packet Classification with Hash Tables

Science.gov (United States)

Wang, Pi-Chung

In the last decade, the technique of packet classification has been widely deployed in various network devices, including routers, firewalls and network intrusion detection systems. In this work, we improve the performance of packet classification by using multiple hash tables. The existing hash-based algorithms have superior scalability with respect to the required space; however, their search performance may not be comparable to other algorithms. To improve the search performance, we propose a tuple reordering algorithm to minimize the number of accessed hash tables with the aid of bitmaps. We also use pre-computation to ensure the accuracy of our search procedure. Performance evaluation based on both real and synthetic filter databases shows that our scheme is effective and scalable and the pre-computation cost is moderate.

Field sampling and data analysis methods for development of ecological land classifications: an application on the Manistee National Forest.

Science.gov (United States)

George E. Host; Carl W. Ramm; Eunice A. Padley; Kurt S. Pregitzer; James B. Hart; David T. Cleland

1992-01-01

Presents technical documentation for development of an Ecological Classification System for the Manistee National Forest in northwest Lower Michigan, and suggests procedures applicable to other ecological land classification projects. Includes discussion of sampling design, field data collection, data summarization and analyses, development of classification units,...

76 FR 80278 - Revision of Cotton Classification Procedures for Determining Cotton Leaf Grade

Science.gov (United States)

2011-12-23

... challenge to the provisions of this rule. Regulatory Flexibility Act Pursuant to requirements set forth in... currently part of the official USDA cotton classification. Accurate assignment of leaf grade is of economic... cost factor associated with its removal. Furthermore, since small leaf particles cannot always be...

PROGRESSIVE DENSIFICATION AND REGION GROWING METHODS FOR LIDAR DATA CLASSIFICATION

Directory of Open Access Journals (Sweden)

J. L. Pérez-García

2012-07-01

Full Text Available At present, airborne laser scanner systems are one of the most frequent methods used to obtain digital terrain elevation models. While having the advantage of direct measurement on the object, the point cloud obtained has the need for classification of their points according to its belonging to the ground. This need for classification of raw data has led to appearance of multiple filters focused LiDAR classification information. According this approach, this paper presents a classification method that combines LiDAR data segmentation techniques and progressive densification to carry out the location of the points belonging to the ground. The proposed methodology is tested on several datasets with different terrain characteristics and data availability. In all case, we analyze the advantages and disadvantages that have been obtained compared with the individual techniques application and, in a special way, the benefits derived from the integration of both classification techniques. In order to provide a more comprehensive quality control of the classification process, the obtained results have been compared with the derived from a manual procedure, which is used as reference classification. The results are also compared with other automatic classification methodologies included in some commercial software packages, highly contrasted by users for LiDAR data treatment.

Exploiting unsupervised and supervised classification for segmentation of the pathological lung in CT

International Nuclear Information System (INIS)

Korfiatis, P; Costaridou, L; Kalogeropoulou, C; Petsas, T; Daoussis, D; Adonopoulos, A

2009-01-01

Delineation of lung fields in presence of diffuse lung diseases (DLPDs), such as interstitial pneumonias (IP), challenges segmentation algorithms. To deal with IP patterns affecting the lung border an automated image texture classification scheme is proposed. The proposed segmentation scheme is based on supervised texture classification between lung tissue (normal and abnormal) and surrounding tissue (pleura and thoracic wall) in the lung border region. This region is coarsely defined around an initial estimate of lung border, provided by means of Markov Radom Field modeling and morphological operations. Subsequently, a support vector machine classifier was trained to distinguish between the above two classes of tissue, using textural feature of gray scale and wavelet domains. 17 patients diagnosed with IP, secondary to connective tissue diseases were examined. Segmentation performance in terms of overlap was 0.924±0.021, and for shape differentiation mean, rms and maximum distance were 1.663±0.816, 2.334±1.574 and 8.0515±6.549 mm, respectively. An accurate, automated scheme is proposed for segmenting abnormal lung fields in HRC affected by IP

Exploiting unsupervised and supervised classification for segmentation of the pathological lung in CT

Science.gov (United States)

Korfiatis, P.; Kalogeropoulou, C.; Daoussis, D.; Petsas, T.; Adonopoulos, A.; Costaridou, L.

2009-07-01

Delineation of lung fields in presence of diffuse lung diseases (DLPDs), such as interstitial pneumonias (IP), challenges segmentation algorithms. To deal with IP patterns affecting the lung border an automated image texture classification scheme is proposed. The proposed segmentation scheme is based on supervised texture classification between lung tissue (normal and abnormal) and surrounding tissue (pleura and thoracic wall) in the lung border region. This region is coarsely defined around an initial estimate of lung border, provided by means of Markov Radom Field modeling and morphological operations. Subsequently, a support vector machine classifier was trained to distinguish between the above two classes of tissue, using textural feature of gray scale and wavelet domains. 17 patients diagnosed with IP, secondary to connective tissue diseases were examined. Segmentation performance in terms of overlap was 0.924±0.021, and for shape differentiation mean, rms and maximum distance were 1.663±0.816, 2.334±1.574 and 8.0515±6.549 mm, respectively. An accurate, automated scheme is proposed for segmenting abnormal lung fields in HRC affected by IP

Soft tissue grafting to improve implant esthetics

Directory of Open Access Journals (Sweden)

Moawia M Kassab

2010-09-01

Full Text Available Moawia M KassabDivision of Periodontics, Marquette University, School of Dentistry, Milwaukee, WI, USAAbstract: Dental implants are becoming the treatment of choice to replace missing teeth, especially if the adjacent teeth are free of restorations. When minimal bone width is present, implant placement becomes a challenge and often resulting in recession and dehiscence around the implant that leads to subsequent gingival recession. To correct such defect, the author turned to soft tissue autografting and allografting to correct a buccal dehiscence around tooth #24 after a malpositioned implant placed by a different surgeon. A 25-year-old woman presented with the chief complaint of gingival recession and exposure of implant threads around tooth #24. The patient received three soft tissue grafting procedures to augment the gingival tissue. The first surgery included a connective tissue graft to increase the width of the keratinized gingival tissue. The second surgery included the use of autografting (connective tissue graft to coronally position the soft tissue and achieve implant coverage. The third and final surgery included the use of allografting material Alloderm to increase and mask the implant from showing through the gingiva. Healing period was uneventful for the patient. After three surgical procedures, it appears that soft tissue grafting has increased the width and height of the gingiva surrounding the implant. The accomplished thickness of gingival tissue appeared to mask the showing of implant threads through the gingival tissue and allowed for achieving the desired esthetic that the patient desired. The aim of the study is to present a clinical case with soft tissue grafting procedures.Keywords: case report, connective tissue, dental implants, allograft, coronally positioned flap

Dynamic Principal Component Analysis with Nonoverlapping Moving Window and Its Applications to Epileptic EEG Classification

Directory of Open Access Journals (Sweden)

Shengkun Xie

2014-01-01

Full Text Available Classification of electroencephalography (EEG is the most useful diagnostic and monitoring procedure for epilepsy study. A reliable algorithm that can be easily implemented is the key to this procedure. In this paper a novel signal feature extraction method based on dynamic principal component analysis and nonoverlapping moving window is proposed. Along with this new technique, two detection methods based on extracted sparse features are applied to deal with signal classification. The obtained results demonstrated that our proposed methodologies are able to differentiate EEGs from controls and interictal for epilepsy diagnosis and to separate EEGs from interictal and ictal for seizure detection. Our approach yields high classification accuracy for both single-channel short-term EEGs and multichannel long-term EEGs. The classification performance of the method is also compared with other state-of-the-art techniques on the same datasets and the effect of signal variability on the presented methods is also studied.

Classification of perovskites with supervised self-organizing maps

International Nuclear Information System (INIS)

Kuzmanovski, Igor; Dimitrovska-Lazova, Sandra; Aleksovska, Slobotka

2007-01-01

In this work supervised self-organizing maps were used for structural classification of perovskites. For this purpose, structural data for total number of 286 perovskites, belonging to ABO 3 and/or A 2 BB'O 6 types, were collected from literature: 130 of these are cubic, 85 orthorhombic and 71 monoclinic. For classification purposes, the effective ionic radii of the cations, electronegativities of the cations in B-position, as well as, the oxidation states of these cations, were used as input variables. The parameters of the developed models, as well as, the most suitable variables for classification purposes were selected using genetic algorithms. Two-third of all the compounds were used in the training phase. During the optimization process the performances of the models were checked using cross-validation leave-1/10-out. The performances of obtained solutions were checked using the test set composed of the remaining one-third of the compounds. The obtained models for classification of these three classes of perovskite compounds show very good results. Namely, the classification of the compounds in the test set resulted in small number of discrepancies (4.2-6.4%) between the actual crystallographic class and the one predicted by the models. All these results are strong arguments for the validity of supervised self-organizing maps for performing such types of classification. Therefore, the proposed procedure could be successfully used for crystallographic classification of perovskites in one of these three classes

Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

Science.gov (United States)

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. Approach. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. Main results. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. Significance. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Genesis of theory and analysis of practice of applying the analytical procedures in auditing

OpenAIRE

Сурніна, К. С.

2012-01-01

Determination of concept "Analytical procedures" in an audit by different researchers is investigated in the article, ownvision of necessity of wideuse of analytical procedures in audit is defined. Classification of analytical procedures is presentedtaking into account the specifity of auditing process on the whole

Morphological classification of plant cell deaths.

Science.gov (United States)

van Doorn, W G; Beers, E P; Dangl, J L; Franklin-Tong, V E; Gallois, P; Hara-Nishimura, I; Jones, A M; Kawai-Yamada, M; Lam, E; Mundy, J; Mur, L A J; Petersen, M; Smertenko, A; Taliansky, M; Van Breusegem, F; Wolpert, T; Woltering, E; Zhivotovsky, B; Bozhkov, P V

2011-08-01

Programmed cell death (PCD) is an integral part of plant development and of responses to abiotic stress or pathogens. Although the morphology of plant PCD is, in some cases, well characterised and molecular mechanisms controlling plant PCD are beginning to emerge, there is still confusion about the classification of PCD in plants. Here we suggest a classification based on morphological criteria. According to this classification, the use of the term 'apoptosis' is not justified in plants, but at least two classes of PCD can be distinguished: vacuolar cell death and necrosis. During vacuolar cell death, the cell contents are removed by a combination of autophagy-like process and release of hydrolases from collapsed lytic vacuoles. Necrosis is characterised by early rupture of the plasma membrane, shrinkage of the protoplast and absence of vacuolar cell death features. Vacuolar cell death is common during tissue and organ formation and elimination, whereas necrosis is typically found under abiotic stress. Some examples of plant PCD cannot be ascribed to either major class and are therefore classified as separate modalities. These are PCD associated with the hypersensitive response to biotrophic pathogens, which can express features of both necrosis and vacuolar cell death, PCD in starchy cereal endosperm and during self-incompatibility. The present classification is not static, but will be subject to further revision, especially when specific biochemical pathways are better defined.

Spiral waves characterization: Implications for an automated cardiodynamic tissue characterization.

Science.gov (United States)

Alagoz, Celal; Cohen, Andrew R; Frisch, Daniel R; Tunç, Birkan; Phatharodom, Saran; Guez, Allon

2018-07-01

Spiral waves are phenomena observed in cardiac tissue especially during fibrillatory activities. Spiral waves are revealed through in-vivo and in-vitro studies using high density mapping that requires special experimental setup. Also, in-silico spiral wave analysis and classification is performed using membrane potentials from entire tissue. In this study, we report a characterization approach that identifies spiral wave behaviors using intracardiac electrogram (EGM) readings obtained with commonly used multipolar diagnostic catheters that perform localized but high-resolution readings. Specifically, the algorithm is designed to distinguish between stationary, meandering, and break-up rotors. The clustering and classification algorithms are tested on simulated data produced using a phenomenological 2D model of cardiac propagation. For EGM measurements, unipolar-bipolar EGM readings from various locations on tissue using two catheter types are modeled. The distance measure between spiral behaviors are assessed using normalized compression distance (NCD), an information theoretical distance. NCD is a universal metric in the sense it is solely based on compressibility of dataset and not requiring feature extraction. We also introduce normalized FFT distance (NFFTD) where compressibility is replaced with a FFT parameter. Overall, outstanding clustering performance was achieved across varying EGM reading configurations. We found that effectiveness in distinguishing was superior in case of NCD than NFFTD. We demonstrated that distinct spiral activity identification on a behaviorally heterogeneous tissue is also possible. This report demonstrates a theoretical validation of clustering and classification approaches that provide an automated mapping from EGM signals to assessment of spiral wave behaviors and hence offers a potential mapping and analysis framework for cardiac tissue wavefront propagation patterns. Copyright © 2018 Elsevier B.V. All rights reserved.

Classifying Classifications

DEFF Research Database (Denmark)

Debus, Michael S.

2017-01-01

This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

Land-Use and Land-Cover Mapping Using a Gradable Classification Method

Directory of Open Access Journals (Sweden)

Keigo Kitada

2012-05-01

Full Text Available Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a group of pixels should be considered. Lacunarity is an index used to characterize different texture appearances. It is often reported that the land-use and land-cover in urban areas can be effectively classified using the lacunarity index with high-resolution images. However, the applicability of the maximum-likelihood approach for hybrid analysis has not been reported. A more effective approach that employs the original spectral data and lacunarity index can be expected to improve the accuracy of the classification. A new classification procedure referred to as “gradable classification method” is proposed in this study. This method improves the classification accuracy in incremental steps. The proposed classification approach integrates several classification maps created from original images and lacunarity maps, which consist of lacnarity values, to create a new classification map. The results of this study confirm the suitability of the gradable classification approach, which produced a higher overall accuracy (68% and kappa coefficient (0.64 than those (65% and 0.60, respectively obtained with the maximum-likelihood approach.

Torrent classification - Base of rational management of erosive regions

International Nuclear Information System (INIS)

Gavrilovic, Zoran; Stefanovic, Milutin; Milovanovic, Irina; Cotric, Jelena; Milojevic, Mileta

2008-01-01

A complex methodology for torrents and erosion and the associated calculations was developed during the second half of the twentieth century in Serbia. It was the 'Erosion Potential Method'. One of the modules of that complex method was focused on torrent classification. The module enables the identification of hydro graphic, climate and erosion characteristics. The method makes it possible for each torrent, regardless of its magnitude, to be simply and recognizably described by the 'Formula of torrentially'. The above torrent classification is the base on which a set of optimisation calculations is developed for the required scope of erosion-control works and measures, the application of which enables the management of significantly larger erosion and torrential regions compared to the previous period. This paper will present the procedure and the method of torrent classification.

Inguinal hernia recurrence: Classification and approach

Directory of Open Access Journals (Sweden)

Campanelli Giampiero

2006-01-01

Full Text Available The authors reviewed the records of 2,468 operations of groin hernia in 2,350 patients, including 277 recurrent hernias updated to January 2005. The data obtained - evaluating technique, results and complications - were used to propose a simple anatomo-clinical classification into three types which could be used to plan the surgical strategy:Type R1: first recurrence ′high,′ oblique external, reducible hernia with small (< 2 cm defect in non-obese patients, after pure tissue or mesh repairType R2: first recurrence ′low,′ direct, reducible hernia with small (< 2 cm defect in non-obese patients, after pure tissue or mesh repairType R3: all the other recurrences - including femoral recurrences; recurrent groin hernia with big defect (inguinal eventration; multirecurrent hernias; nonreducible, linked with a controlateral primitive or recurrent hernia; and situations compromised from aggravating factors (for example obesity or anyway not easily included in R1 or R2, after pure tissue or mesh repair.

Classification of multiple sclerosis lesions using adaptive dictionary learning.

Science.gov (United States)

Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

2015-12-01

This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development and validation of a gas chromatography/mass spectrometry procedure for confirmation of para-toluenesulfonamide in edible fish fillet tissue.

Science.gov (United States)

Idowu, Olutosin R; Kijak, Philip J; Meinertz, Jeffery R; Schmidt, Larry J

2004-01-01

Chloramine-T is a disinfectant being developed as a treatment for bacterial gill disease in cultured fish. As part of the drug approval process, a method is required for the confirmation of chloramine-T residues in edible fish tissue. The marker residue that will be used to determine the depletion of chloramine-T residues from the edible tissue of treated fish is para-toluenesulfonamide (p-TSA), a metabolite of chloramine-T. The development and validation of a procedure for the confirmation of p-TSA is described. Homogenized fish tissue is dried by mixing with anhydrous sodium sulfate, and the mixture is extracted with methylene chloride. The extract is passed through a silica gel solid-phase extraction column, from which p-TSA is subsequently eluted with acetonitrile. The acetonitrile extract is evaporated, and the oily residue is dissolved in hexane. The hexane solution is shaken with fresh acetonitrile. The acetonitrile solution is evaporated and the residue is redissolved in dilute potassium hydroxide solution. The aqueous solution is extracted with methylene chloride to further remove more of the fat co-extractive. The aqueous solution is reacted with pentafluorobenzyl bromide in presence of tetrabutylammonium hydrogensulfate. The resulting di-(pentafluorobenzyl) derivative of p-TSA is analyzed by gas chromatography/mass spectrometry. This method permits the confirmation of p-TSA in edible fish tissue at 20 ppb.

What does the activation of a classification and decontamination station involve?

International Nuclear Information System (INIS)

2002-01-01

On 1 October 1999, the Council of Ministers adopted a resolution urging the Nuclear Safety Council to inform the public on the health protection measures to take and the procedure to follow in a radiological emergency. The content of this articles describes the activation and work of stations for the classification and decontamination of persons, a procedure provided for in the Provincial Nuclear Emergency Plans. (Author)

The value of laparoscopic classifications in decision on definitive ...

African Journals Online (AJOL)

The value of laparoscopic classifications in decision on definitive surgery in patients with nonpalpable testes: our ... present our clinical experience with the laparoscopic approach in patients with nonpalpable testes (NPTs) and .... decision making during the procedure. Gatti and. Ostlie [3] have pointed out that laparoscopic ...

REAL-TIME INTELLIGENT MULTILAYER ATTACK CLASSIFICATION SYSTEM

Directory of Open Access Journals (Sweden)

T. Subbhulakshmi

2014-01-01

Full Text Available Intrusion Detection Systems (IDS takes the lion’s share of the current security infrastructure. Detection of intrusions is vital for initiating the defensive procedures. Intrusion detection was done by statistical and distance based methods. A threshold value is used in these methods to indicate the level of normalcy. When the network traffic crosses the level of normalcy then above which it is flagged as anomalous. When there are occurrences of new intrusion events which are increasingly a key part of system security, the statistical techniques cannot detect them. To overcome this issue, learning techniques are used which helps in identifying new intrusion activities in a computer system. The objective of the proposed system designed in this paper is to classify the intrusions using an Intelligent Multi Layered Attack Classification System (IMLACS which helps in detecting and classifying the intrusions with improved classification accuracy. The intelligent multi layered approach contains three intelligent layers. The first layer involves Binary Support Vector Machine classification for detecting the normal and attack. The second layer involves neural network classification to classify the attacks into classes of attacks. The third layer involves fuzzy inference system to classify the attacks into various subclasses. The proposed IMLACS can be able to detect an intrusion behavior of the networks since the system contains a three intelligent layer classification and better set of rules. Feature selection is also used to improve the time of detection. The experimental results show that the IMLACS achieves the Classification Rate of 97.31%.

Tissue quantification for development of pediatric phantom

International Nuclear Information System (INIS)

Alves, A.F.F.; Miranda, J.R.A.; Pina, D.R.

2013-01-01

The optimization of the risk- benefit ratio is a major concern in the pediatric radiology, due to the greater vulnerability of children to the late somatic effects and genetic effects of exposure to radiation compared to adults. In Brazil, it is estimated that the causes of death from head trauma are 18 % for the age group between 1-5 years and the radiograph is the primary diagnostic test for the detection of skull fracture . Knowing that the image quality is essential to ensure the identification of structures anatomical and minimizing errors diagnostic interpretation, this paper proposed the development and construction of homogeneous phantoms skull, for the age group 1-5 years. The construction of the phantoms homogeneous was performed using the classification and quantification of tissue present in the skull of pediatric patients. In this procedure computational algorithms were used, using Matlab, to quantify distinct biological tissues present in the anatomical regions studied , using pictures retrospective CT scans. Preliminary data obtained from measurements show that between the ages of 1-5 years, assuming an average anteroposterior diameter of the pediatric skull region of the 145.73 ± 2.97 mm, can be represented by 92.34 mm ± 5.22 of lucite and 1.75 ± 0:21 mm of aluminum plates of a provision of PEP (Pacient equivalent phantom). After its construction, the phantoms will be used for image and dose optimization in pediatric protocols process to examinations of computerized radiography

Categorization of intraoperative ureteroscopy complications using modified Satava classification system.

Science.gov (United States)

Tepeler, Abdulkadir; Resorlu, Berkan; Sahin, Tolga; Sarikaya, Selcuk; Bayindir, Mirze; Oguz, Ural; Armagan, Abdullah; Unsal, Ali

2014-02-01

To review our experience with ureteroscopy (URS) in the treatment of ureteral calculi and stratify intraoperative complications of URS according to the modified Satava classification system. We performed a retrospective analysis of 1,208 patients (672 males and 536 females), with a mean age of 43.1 years (range 1-78), who underwent ureteroscopic procedures for removal of ureteral stones. Intraoperative complications were recorded according to modified Satava classification system. Grade 1 complications included incidents without consequences for the patient; grade 2 complications, which are treated intraoperatively with endoscopic surgery (grade 2a) or required endoscopic re-treatment (grade 2b); and grade 3 complications included incidents requiring open or laparoscopic surgery. The stones were completely removed in 1,067 (88.3%) patients after primary procedure by either simple extraction or after fragmentation. The overall incidence of intraoperative complications was 12.6%. The most common complications were proximal stone migration (3.9%), mucosal injury (2.8%), bleeding (1.9%), inability to reach stone (1.8%), malfunctioning or breakage of instruments (0.8%), ureteral perforation (0.8%) and ureteral avulsion (0.16%). According to modified Satava classification system, there were 4.5% grade 1; 4.4% grade 2a; 3.2% grade 2b; and 0.57% grade 3 complications. We think that modified Satava classification is a quick and simple system for describing the severity of intraoperative URS complications and this grading system will facilitate a better comparison for the surgical outcomes obtained from different centers.

Multispectral tissue characterization for intestinal anastomosis optimization

Science.gov (United States)

Cha, Jaepyeong; Shademan, Azad; Le, Hanh N. D.; Decker, Ryan; Kim, Peter C. W.; Kang, Jin U.; Krieger, Axel

2015-10-01

Intestinal anastomosis is a surgical procedure that restores bowel continuity after surgical resection to treat intestinal malignancy, inflammation, or obstruction. Despite the routine nature of intestinal anastomosis procedures, the rate of complications is high. Standard visual inspection cannot distinguish the tissue subsurface and small changes in spectral characteristics of the tissue, so existing tissue anastomosis techniques that rely on human vision to guide suturing could lead to problems such as bleeding and leakage from suturing sites. We present a proof-of-concept study using a portable multispectral imaging (MSI) platform for tissue characterization and preoperative surgical planning in intestinal anastomosis. The platform is composed of a fiber ring light-guided MSI system coupled with polarizers and image analysis software. The system is tested on ex vivo porcine intestine tissue, and we demonstrate the feasibility of identifying optimal regions for suture placement.

Disease Classification and Biomarker Discovery Using ECG Data

Directory of Open Access Journals (Sweden)

Rong Huang

2015-01-01

Full Text Available In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA, SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively.

Sensitivity and Specificity of Cardiac Tissue Discrimination Using Fiber-Optics Confocal Microscopy.

Science.gov (United States)

Huang, Chao; Sachse, Frank B; Hitchcock, Robert W; Kaza, Aditya K

2016-01-01

Disturbances of the cardiac conduction system constitute a major risk after surgical repair of complex cases of congenital heart disease. Intraoperative identification of the conduction system may reduce the incidence of these disturbances. We previously developed an approach to identify cardiac tissue types using fiber-optics confocal microscopy and extracellular fluorophores. Here, we applied this approach to investigate sensitivity and specificity of human and automated classification in discriminating images of atrial working myocardium and specialized tissue of the conduction system. Two-dimensional image sequences from atrial working myocardium and nodal tissue of isolated perfused rodent hearts were acquired using a fiber-optics confocal microscope (Leica FCM1000). We compared two methods for local application of extracellular fluorophores: topical via pipette and with a dye carrier. Eight blinded examiners evaluated 162 randomly selected images of atrial working myocardium (n = 81) and nodal tissue (n = 81). In addition, we evaluated the images using automated classification. Blinded examiners achieved a sensitivity and specificity of 99.2 ± 0.3% and 98.0 ± 0.7%, respectively, with the dye carrier method of dye application. Sensitivity and specificity was similar for dye application via a pipette (99.2 ± 0.3% and 94.0 ± 2.4%, respectively). Sensitivity and specificity for automated methods of tissue discrimination were similarly high. Human and automated classification achieved high sensitivity and specificity in discriminating atrial working myocardium and nodal tissue. We suggest that our findings facilitate clinical translation of fiber-optics confocal microscopy as an intraoperative imaging modality to reduce the incidence of conduction disturbances during surgical correction of congenital heart disease.

Assessment and classification of psychopathology in epidemiological research of children 0-3 years of age: a review of the literature

DEFF Research Database (Denmark)

Skovgaard, A M; Houmann, T; Landorph, S L

2004-01-01

, such as the Bayley Scales, and relationship assessments, such as the Early Relational Assessment (ERA). The classification of psychopathology in young children can be approved by the Diagnostic Classification 0-3. The reliability and validity of DC 0-3 have not yet been established, but preliminary results seem...... promising. The demands made on diagnostic assessment procedures in epidemiological research of children 0-3 years of age can be met by a combination of well-established research instruments, such as the CBCL, with in-depth clinical assessment procedures, such as the Bayley Scales and the ERA, and diagnostic...... classification by DC 0-3....

PATMA: parser of archival tissue microarray

Directory of Open Access Journals (Sweden)

Lukasz Roszkowiak

2016-12-01

Full Text Available Tissue microarrays are commonly used in modern pathology for cancer tissue evaluation, as it is a very potent technique. Tissue microarray slides are often scanned to perform computer-aided histopathological analysis of the tissue cores. For processing the image, splitting the whole virtual slide into images of individual cores is required. The only way to distinguish cores corresponding to specimens in the tissue microarray is through their arrangement. Unfortunately, distinguishing the correct order of cores is not a trivial task as they are not labelled directly on the slide. The main aim of this study was to create a procedure capable of automatically finding and extracting cores from archival images of the tissue microarrays. This software supports the work of scientists who want to perform further image processing on single cores. The proposed method is an efficient and fast procedure, working in fully automatic or semi-automatic mode. A total of 89% of punches were correctly extracted with automatic selection. With an addition of manual correction, it is possible to fully prepare the whole slide image for extraction in 2 min per tissue microarray. The proposed technique requires minimum skill and time to parse big array of cores from tissue microarray whole slide image into individual core images.

Classification system of the mineral reserves and resources of Ukraine

International Nuclear Information System (INIS)

Lovinyukov, V.I.

1998-01-01

This paper describes the system used to classify the resources and reserves of all minerals and fuels in Ukraine. The classification system is part of an official procedure determined by the Ukrainian State Commission on Reserves. Following preparation of resource estimates the results are registered with the State, which maintains an official inventory of all mineral resources. This paper compares the Ukrainian system to, and finds it compatible with the United Nations International Framework of resource classification. The UN system is based on economics of production and mineability. (author)

Classification system of the mineral reserves and resources of Ukraine

International Nuclear Information System (INIS)

Lovyunikov, V.I.

1997-01-01

This paper describes the system used to classify the resources and reserves of all minerals and fuels in Ukraine. The classification system is part of an official procedures determined by the Ukrainian State Commission on Reserves. Following preparation of resource estimates the results are registered with the State, which maintains an official inventory of all mineral resources. This paper compares the Ukrainian system to, and finds it compatible with the United Nations International Framework of resources classification. The UN system is based on economics of production and mineability. (author). 1 tab

Random lasing in human tissues

International Nuclear Information System (INIS)

Polson, Randal C.; Vardeny, Z. Valy

2004-01-01

A random collection of scatterers in a gain medium can produce coherent laser emission lines dubbed 'random lasing'. We show that biological tissues, including human tissues, can support coherent random lasing when infiltrated with a concentrated laser dye solution. To extract a typical random resonator size within the tissue we average the power Fourier transform of random laser spectra collected from many excitation locations in the tissue; we verified this procedure by a computer simulation. Surprisingly, we found that malignant tissues show many more laser lines compared to healthy tissues taken from the same organ. Consequently, the obtained typical random resonator was found to be different for healthy and cancerous tissues, and this may lead to a technique for separating malignant from healthy tissues for diagnostic imaging

The Japanese Society of Pathology Guidelines on the handling of pathological tissue samples for genomic research: Standard operating procedures based on empirical analyses.

Science.gov (United States)

Kanai, Yae; Nishihara, Hiroshi; Miyagi, Yohei; Tsuruyama, Tatsuhiro; Taguchi, Kenichi; Katoh, Hiroto; Takeuchi, Tomoyo; Gotoh, Masahiro; Kuramoto, Junko; Arai, Eri; Ojima, Hidenori; Shibuya, Ayako; Yoshida, Teruhiko; Akahane, Toshiaki; Kasajima, Rika; Morita, Kei-Ichi; Inazawa, Johji; Sasaki, Takeshi; Fukayama, Masashi; Oda, Yoshinao

2018-02-01

Genome research using appropriately collected pathological tissue samples is expected to yield breakthroughs in the development of biomarkers and identification of therapeutic targets for diseases such as cancers. In this connection, the Japanese Society of Pathology (JSP) has developed "The JSP Guidelines on the Handling of Pathological Tissue Samples for Genomic Research" based on an abundance of data from empirical analyses of tissue samples collected and stored under various conditions. Tissue samples should be collected from appropriate sites within surgically resected specimens, without disturbing the features on which pathological diagnosis is based, while avoiding bleeding or necrotic foci. They should be collected as soon as possible after resection: at the latest within about 3 h of storage at 4°C. Preferably, snap-frozen samples should be stored in liquid nitrogen (about -180°C) until use. When intending to use genomic DNA extracted from formalin-fixed paraffin-embedded tissue, 10% neutral buffered formalin should be used. Insufficient fixation and overfixation must both be avoided. We hope that pathologists, clinicians, clinical laboratory technicians and biobank operators will come to master the handling of pathological tissue samples based on the standard operating procedures in these Guidelines to yield results that will assist in the realization of genomic medicine. © 2018 The Authors. Pathology International published by Japanese Society of Pathology and John Wiley & Sons Australia, Ltd.

Automated classification of cell morphology by coherence-controlled holographic microscopy

Science.gov (United States)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

Science.gov (United States)

Belgiu, Mariana; ǎguţ, Lucian, , Dr; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Procedures of Operation at Cranbrook Central Library.

Science.gov (United States)

Cranbrook Institutions, Bloomfield Hills, MI. Central Library.

This manual outlines the ordering, cataloging and classification, and processing procedures for books, periodicals, government documents, and non-book materials for a central library serving three schools--a co-ed elementary school and separate junior-senior high schools for boys and girls--and four special libraries--a fine and rare books…

Torrent classification - Base of rational management of erosive regions

Energy Technology Data Exchange (ETDEWEB)

Gavrilovic, Zoran; Stefanovic, Milutin; Milovanovic, Irina; Cotric, Jelena; Milojevic, Mileta [Institute for the Development of Water Resources ' Jaroslav Cerni' , 11226 Beograd (Pinosava), Jaroslava Cernog 80 (Serbia)], E-mail: gavrilovicz@sbb.rs

2008-11-01

A complex methodology for torrents and erosion and the associated calculations was developed during the second half of the twentieth century in Serbia. It was the 'Erosion Potential Method'. One of the modules of that complex method was focused on torrent classification. The module enables the identification of hydro graphic, climate and erosion characteristics. The method makes it possible for each torrent, regardless of its magnitude, to be simply and recognizably described by the 'Formula of torrentially'. The above torrent classification is the base on which a set of optimisation calculations is developed for the required scope of erosion-control works and measures, the application of which enables the management of significantly larger erosion and torrential regions compared to the previous period. This paper will present the procedure and the method of torrent classification.

Search techniques in intelligent classification systems

CERN Document Server

Savchenko, Andrey V

2016-01-01

A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technicall...

Characterization of aerosols produced by surgical procedures: A summary

Energy Technology Data Exchange (ETDEWEB)

Yeh, Hsu-Chi; Muggenburg, B.A.; Lundgren, D.L.; Turner, R.S.; Guilmette, R.A.; Snipes, M.B.; Jones, R.K.

1994-11-01

In many types of surgery, especially orthopedic procedures, power tools such as saws and drills are used. These tools can impart considerable energy in disrupting tissue and may produce aerosolized blood and material from bone and other tissues. Surgical lasers and electrocautery tools can also produce aerosols due to vaporization of blood and tissues. A number of studies have been reported concerning production of aerosols during surgery, and some of the aerosols produced may contain infectious materials. Health care workers have expressed concern and questions pertaining to the occupational transmission of blood-borne pathogens including the human immunodeficiency virus (HIV) and hepatitis B virus (HBV) via blood aerosols during surgery. Little or no data existed characterizing the aerosols produced performing surgical procedures. Because of this lack of data, the National Institute for Occupational Safety and Health funded a project at ITRI to assess the extent of aerosolization of blood and other tissues during surgical procedures in the laboratory and in a hospital surgical suite.

Characterization of aerosols produced by surgical procedures: A summary

International Nuclear Information System (INIS)

Yeh, Hsu-Chi; Muggenburg, B.A.; Lundgren, D.L.; Turner, R.S.; Guilmette, R.A.; Snipes, M.B.; Jones, R.K.

1994-01-01

In many types of surgery, especially orthopedic procedures, power tools such as saws and drills are used. These tools can impart considerable energy in disrupting tissue and may produce aerosolized blood and material from bone and other tissues. Surgical lasers and electrocautery tools can also produce aerosols due to vaporization of blood and tissues. A number of studies have been reported concerning production of aerosols during surgery, and some of the aerosols produced may contain infectious materials. Health care workers have expressed concern and questions pertaining to the occupational transmission of blood-borne pathogens including the human immunodeficiency virus (HIV) and hepatitis B virus (HBV) via blood aerosols during surgery. Little or no data existed characterizing the aerosols produced performing surgical procedures. Because of this lack of data, the National Institute for Occupational Safety and Health funded a project at ITRI to assess the extent of aerosolization of blood and other tissues during surgical procedures in the laboratory and in a hospital surgical suite

Diagnosis with near infrared spectroscopy during minimally invasive procedures

NARCIS (Netherlands)

R. Nachabé (Rami)

2012-01-01

textabstractThe goal of this dissertation is to present the potential of diffuse optical spectroscopy technique to characterize and differentiate types of tissue, including dysplastic and cancerous tissues, when measuring the tissue spectra during a surgical or an interventional procedure under

12 CFR 403.11 - Enforcement and investigation procedures.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Enforcement and investigation procedures. 403.11 Section 403.11 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.11 Enforcement and investigation...

Classification of breast cancer histology images using Convolutional Neural Networks.

Directory of Open Access Journals (Sweden)

Teresa Araújo

Full Text Available Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

A simplified classification system for partially edentulous spaces

Directory of Open Access Journals (Sweden)

Bhandari Aruna J, Bhandari Akshay J

2014-04-01

Full Text Available Background: There is no single universally employed classification system that will specify the exact edentulous situation. Several classification systems exist to group the situation and avoid confusion. Classifications based on edentulous areas, finished restored prostheses, type of direct retainers or fulcrum lines are there. Some are based depending on the placement of the implants. Widely accepted Kennedy Applegate classification does not give any idea about length, span or number of teeth missing. Rule 6 governing the application of Kennedy method states that additional edentulous areas are referred as modification number 1,2 etc. Rule 7 states that extent of the modification is not considered; only the number of edentulous areas is considered. Hence there is a need to modify the Kennedy –Applegate System. Aims: This new classification system is an attempt to modify Kennedy –Applegate System so as to give the exact idea about missing teeth, space, span, side and areas of partially edentulous arches. Methods and Material: This system will provide the information regarding Maxillary or Mandibular partially edentulous arches, Left or Right side, length of the edentulous space, number of teeth missing and whether there will be tooth borne or tooth – tissue borne prosthesis. Conclusions: This classification is easy for application, communication and will also help to design the removable cast partial denture in a better logical and systematic way. Also, this system will give the idea of the edentulous status and the number of missing teeth in fixed, hybrid or implant prosthesis.

Robust through-the-wall radar image classification using a target-model alignment procedure.

Science.gov (United States)

Smith, Graeme E; Mobasseri, Bijan G

2012-02-01

A through-the-wall radar image (TWRI) bears little resemblance to the equivalent optical image, making it difficult to interpret. To maximize the intelligence that may be obtained, it is desirable to automate the classification of targets in the image to support human operators. This paper presents a technique for classifying stationary targets based on the high-range resolution profile (HRRP) extracted from 3-D TWRIs. The dependence of the image on the target location is discussed using a system point spread function (PSF) approach. It is shown that the position dependence will cause a classifier to fail, unless the image to be classified is aligned to a classifier-training location. A target image alignment technique based on deconvolution of the image with the system PSF is proposed. Comparison of the aligned target images with measured images shows the alignment process introducing normalized mean squared error (NMSE) ≤ 9%. The HRRP extracted from aligned target images are classified using a naive Bayesian classifier supported by principal component analysis. The classifier is tested using a real TWRI of canonical targets behind a concrete wall and shown to obtain correct classification rates ≥ 97%. © 2011 IEEE

Laser tissue welding in ophthalmic surgery.

Science.gov (United States)

Rossi, Francesca; Matteini, Paolo; Ratto, Fulvio; Menabuoni, Luca; Lenzetti, Ivo; Pini, Roberto

2008-09-01

Laser welding of ocular tissues is an alternative technique or adjunct to conventional suturing in ophthalmic surgery. It is based on the photothermal interaction of laser light with the main components of the extracellular matrix of connective tissues. The advantages of the welding procedure with respect to standard suturing and stapling are reduced operation times, lesser inflammation, faster healing and increased ability to induce tissue regeneration. The procedure we set up is based on the use of an infrared diode laser in association with the topical application of the chromophore Indocyanine Green. Laser light may be delivered either continuously or in pulses, thus identifying two different techniques that have been applied clinically in various types of transplants of the cornea.

[Classification of cell-based medicinal products and legal implications: An overview and an update].

Science.gov (United States)

Scherer, Jürgen; Flory, Egbert

2015-11-01

In general, cell-based medicinal products do not represent a uniform class of medicinal products, but instead comprise medicinal products with diverse regulatory classification as advanced-therapy medicinal products (ATMP), medicinal products (MP), tissue preparations, or blood products. Due to the legal and scientific consequences of the development and approval of MPs, classification should be clarified as early as possible. This paper describes the legal situation in Germany and highlights specific criteria and concepts for classification, with a focus on, but not limited to, ATMPs and non-ATMPs. Depending on the stage of product development and the specific application submitted to a competent authority, legally binding classification is done by the German Länder Authorities, Paul-Ehrlich-Institut, or European Medicines Agency. On request by the applicants, the Committee for Advanced Therapies may issue scientific recommendations for classification.

IR-360 nuclear power plant safety functions and component classification

International Nuclear Information System (INIS)

Yousefpour, F.; Shokri, F.; Soltani, H.

2010-01-01

The IR-360 nuclear power plant as a 2-loop PWR of 360 MWe power generation capacity is under design in MASNA Company. For design of the IR-360 structures, systems and components (SSCs), the codes and standards and their design requirements must be determined. It is a prerequisite to classify the IR-360 safety functions and safety grade of structures, systems and components correctly for selecting and adopting the suitable design codes and standards. This paper refers to the IAEA nuclear safety codes and standards as well as USNRC standard system to determine the IR-360 safety functions and to formulate the principles of the IR-360 component classification in accordance with the safety philosophy and feature of the IR-360. By implementation of defined classification procedures for the IR-360 SSCs, the appropriate design codes and standards are specified. The requirements of specific codes and standards are used in design process of IR-360 SSCs by design engineers of MASNA Company. In this paper, individual determination of the IR-360 safety functions and definition of the classification procedures and roles are presented. Implementation of this work which is described with example ensures the safety and reliability of the IR-360 nuclear power plant.

IR-360 nuclear power plant safety functions and component classification

Energy Technology Data Exchange (ETDEWEB)

Yousefpour, F., E-mail: fyousefpour@snira.co [Management of Nuclear Power Plant Construction Company (MASNA) (Iran, Islamic Republic of); Shokri, F.; Soltani, H. [Management of Nuclear Power Plant Construction Company (MASNA) (Iran, Islamic Republic of)

2010-10-15

The IR-360 nuclear power plant as a 2-loop PWR of 360 MWe power generation capacity is under design in MASNA Company. For design of the IR-360 structures, systems and components (SSCs), the codes and standards and their design requirements must be determined. It is a prerequisite to classify the IR-360 safety functions and safety grade of structures, systems and components correctly for selecting and adopting the suitable design codes and standards. This paper refers to the IAEA nuclear safety codes and standards as well as USNRC standard system to determine the IR-360 safety functions and to formulate the principles of the IR-360 component classification in accordance with the safety philosophy and feature of the IR-360. By implementation of defined classification procedures for the IR-360 SSCs, the appropriate design codes and standards are specified. The requirements of specific codes and standards are used in design process of IR-360 SSCs by design engineers of MASNA Company. In this paper, individual determination of the IR-360 safety functions and definition of the classification procedures and roles are presented. Implementation of this work which is described with example ensures the safety and reliability of the IR-360 nuclear power plant.

A systematic review on soft-to-hard tissue ratios in orthognathic surgery part II: Chin procedures.

Science.gov (United States)

San Miguel Moragas, Joan; Oth, Olivier; Büttner, Michael; Mommaerts, Maurice Y

2015-10-01

Precise soft-to-hard tissue ratios in orthofacial chin procedures are not well established. The aim of this study was to determine useful soft-to-hard tissue ratios for planning the magnitude of sliding genioplasty (chin osteotomy), osseous chin recontouring and alloplastic chin augmentation. A systematic review of English and non-English articles using PubMed central, ProQuest Dissertations and Theses, Science Citation Index, Elsevier Science Direct Complete, Highwire Press, Springer Standard Collection, SAGE premier 2011, DOAJ Directory of Open Access Journals, Sweetswise, Free E-Journals, Ovid Lippincott Williams & Wilkins total Access Collection, Wiley Online Library Journals, and Cochrane Plus databases from their onset until July 2014. Additional studies were identified by searching the references. Search terms included soft tissue, ratios, genioplasty, mentoplasty, chin, genial AND advancement, augmentation, setback, retrusion, impaction, reduction, vertical deficit, widening, narrowing, and expansion. Study selection criteria were as follows: only academic publications; human patients; no reviews; systematic reviews or meta-analyses; no cadavers; no syndromic patients; no pathology at the chin or mandible region; only articles of level of evidence from I to IV; number of patients must be cited in the articles; hard-to-soft tissue ratios must be cited in the articles or at least are able to be calculated with the quantitative data available in the article; if all patients of one article have had bilateral sagittal split osteotomy (BSSO) performed along with chin osteotomy, there should be an independent group evaluation of the data concerning to the chin; and no restriction regarding the size of the group. Independent extraction of articles by two authors using predefined data fields, including study quality indicators (level of evidence). The search identified 22 articles. Eleven additional articles were found in their reference sections. Of these, two were

Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization

Directory of Open Access Journals (Sweden)

Philipp Kainz

2017-10-01

Full Text Available Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN for pixel-wise classification of Hematoxylin-Eosin stained images. While the first classifier separates glands from background, the second classifier identifies gland-separating structures. In a subsequent step, a figure-ground segmentation based on weighted total variation produces the final segmentation result by regularizing the CNN predictions. We present both quantitative and qualitative segmentation results on the recently released and publicly available Warwick-QU colon adenocarcinoma dataset associated with the GlaS@MICCAI2015 challenge and compare our approach to the simultaneously developed other approaches that participated in the same challenge. On two test sets, we demonstrate our segmentation performance and show that we achieve a tissue classification accuracy of 98% and 95%, making use of the inherent capability of our system to distinguish between benign and malignant tissue. Our results show that deep learning approaches can yield highly accurate and reproducible results for biomedical image analysis, with the potential to significantly improve the quality and speed of medical diagnoses.

Notification: Follow-up Review of EPA’s Classification of National Security Information

Science.gov (United States)

Project #OPE-FY15-0057, July 20, 2015. The EPA OIG plans to begin preliminary research on the OARM actions taken to improve policies and procedures related to the classification of national security information.

The linear attenuation coefficients as features of multiple energy CT image classification

International Nuclear Information System (INIS)

Homem, M.R.P.; Mascarenhas, N.D.A.; Cruvinel, P.E.

2000-01-01

We present in this paper an analysis of the linear attenuation coefficients as useful features of single and multiple energy CT images with the use of statistical pattern classification tools. We analyzed four CT images through two pointwise classifiers (the first classifier is based on the maximum-likelihood criterion and the second classifier is based on the k-means clustering algorithm) and one contextual Bayesian classifier (ICM algorithm - Iterated Conditional Modes) using an a priori Potts-Strauss model. A feature extraction procedure using the Jeffries-Matusita (J-M) distance and the Karhunen-Loeve transformation was also performed. Both the classification and the feature selection procedures were found to be in agreement with the predicted discrimination given by the separation of the linear attenuation coefficient curves for different materials

Automatic procedure go keep updated the activity levels for each radionuclide existing in a radioactivity laboratory

International Nuclear Information System (INIS)

Los Arcos, J.M.

1988-01-01

An automatic procedure to keep updated the activity levels each radionuclide existing in a radioactivity laboratory, and its classification according to the Spanish Regulations on Nuclear and Radioactive Establishments is described. This procedure takes into account the mixed composition of each source and whether it is sealed or the activity and mass variation due to extraction or evaporation in non-sealed sources. For a given date and time, the procedure prints out a complete listing of the activity of each radioactive source, the accumulated activity for each radionuclide, for each kind of radionuclide and the actual classification of the laboratory according to the legal regulations above mentioned. (Author)

Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides.

Science.gov (United States)

Torrens, Francisco; Castellano, Gloria

2014-06-05

Pesticide residues in wine were analyzed by liquid chromatography-tandem mass spectrometry. Retentions are modelled by structure-property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy-morphological determination-natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.

Securing classification and regulatory approval for deepwater projects: management challenges in a global environment

Energy Technology Data Exchange (ETDEWEB)

Feijo, Luiz P.; Burton, Gareth C. [American Bureau of Shipping (ABS), Rio de Janeiro, RJ (Brazil)

2008-07-01

As the offshore industry continues to develop and move into increasingly deeper waters, technological boundaries are being pushed to new limits. Along with these advances, the design, fabrication and installation of deepwater oil and gas projects has become an increasingly global endeavor. After providing an overview of the history and role of Classification Societies, this paper reviews the challenges of securing classification and regulatory approval in a global environment. Operational, procedural and technological changes which one Classification Society; the American Bureau of Shipping, known as ABS, has implemented to address these challenges are presented. The result of the changes has been a more customized service aiming at faster and more streamlined classification approval process. (author)

Formalizing the Austrian Procedure Catalogue: A 4-step methodological analysis approach.

Science.gov (United States)

Neururer, Sabrina Barbara; Lasierra, Nelia; Peiffer, Karl Peter; Fensel, Dieter

2016-04-01

Due to the lack of an internationally accepted and adopted standard for coding health interventions, Austria has established its own country-specific procedure classification system - the Austrian Procedure Catalogue (APC). Even though the APC is an elaborate coding standard for medical procedures, it has shortcomings that limit its usability. In order to enhance usability and usefulness, especially for research purposes and e-health applications, we developed an ontologized version of the APC. In this paper we present a novel four-step approach for the ontology engineering process, which enables accurate extraction of relevant concepts for medical ontologies from written text. The proposed approach for formalizing the APC consists of the following four steps: (1) comparative pre-analysis, (2) definition analysis, (3) typological analysis, and (4) ontology implementation. The first step contained a comparison of the APC to other well-established or elaborate health intervention coding systems in order to identify strengths and weaknesses of the APC. In the second step, a list of definitions of medical terminology used in the APC was obtained. This list of definitions was used as input for Step 3, in which we identified the most important concepts to describe medical procedures using the qualitative typological analysis approach. The definition analysis as well as the typological analysis are well-known and effective methods used in social sciences, but not commonly employed in the computer science or ontology engineering domain. Finally, this list of concepts was used in Step 4 to formalize the APC. The pre-analysis highlighted the major shortcomings of the APC, such as the lack of formal definition, leading to implicitly available, but not directly accessible information (hidden data), or the poor procedural type classification. After performing the definition and subsequent typological analyses, we were able to identify the following main characteristics of

Recursive Cluster Elimination (RCE for classification and feature selection from gene expression data

Directory of Open Access Journals (Sweden)

Showe Louise C

2007-05-01

Full Text Available Abstract Background Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that are important for distinguishing the different sample classes being compared, poses a challenging problem in high dimensional data analysis. We describe a new procedure for selecting significant genes as recursive cluster elimination (RCE rather than recursive feature elimination (RFE. We have tested this algorithm on six datasets and compared its performance with that of two related classification procedures with RFE. Results We have developed a novel method for selecting significant genes in comparative gene expression studies. This method, which we refer to as SVM-RCE, combines K-means, a clustering method, to identify correlated gene clusters, and Support Vector Machines (SVMs, a supervised machine learning classification method, to identify and score (rank those gene clusters for the purpose of classification. K-means is used initially to group genes into clusters. Recursive cluster elimination (RCE is then applied to iteratively remove those clusters of genes that contribute the least to the classification performance. SVM-RCE identifies the clusters of correlated genes that are most significantly differentially expressed between the sample classes. Utilization of gene clusters, rather than individual genes, enhances the supervised classification accuracy of the same data as compared to the accuracy when either SVM or Penalized Discriminant Analysis (PDA with recursive feature elimination (SVM-RFE and PDA-RFE are used to remove genes based on their individual discriminant weights. Conclusion SVM-RCE provides improved classification accuracy with complex microarray data sets when it is compared to the classification accuracy of the same datasets using either SVM-RFE or PDA-RFE. SVM-RCE identifies clusters of correlated genes that when considered together

Soft tissue expansion before vertical ridge augmentation: Inflatable silicone balloons or self-filling osmotic tissue expanders?

Directory of Open Access Journals (Sweden)

Prasad Vijayrao Dhadse

2014-01-01

Full Text Available Recent advances in periodontal plastic surgical procedures allow the clinician to reconstruct deficient alveolar ridges in more predictable ways than previously possible. Placement of implant/s in resorbed ridges poses numerous challenges to the clinician for successful esthetic and functional rehabilitation. The reconstruction frequently utilizes one or combination of periodontal plastic surgical procedures in conjunction with autogenous bone grafting, allogenic bone block grafting, ridge split techniques, distraction osteogenesis, or guided bone regeneration (GBR for most predictable outcomes. Current surgical modalities used in reconstruction of alveolar ridge (horizontal and/or vertical component often involve the need of flap transfer. Moreover, there is compromise in tissue integrity and color match owing to different surgical site and the tissue utilized is insufficient in quantity leading to post surgical graft exposition and/or loss of grafted bone. Soft tissue expansion (STE by implantation of inflatable silicone balloon or self filling osmotic tissue expanders before reconstructive surgery can overcome these disadvantages and certainly holds a promise for effective method for generation of soft tissue thereby achieving predictable augmentation of deficient alveolar ridges for the implant success. This article focuses and compares these distinct tissue expanders for their clinical efficacy of achieving excess tissue that predominantly seems to be prerequisite for ridge augmentation which can be reasonably followed by successful placement of endosseous fixtures.

Fourier Transform Infrared (FT-IR) and Laser Ablation Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) Imaging of Cerebral Ischemia: Combined Analysis of Rat Brain Thin Cuts Toward Improved Tissue Classification.

Science.gov (United States)

Balbekova, Anna; Lohninger, Hans; van Tilborg, Geralda A F; Dijkhuizen, Rick M; Bonta, Maximilian; Limbeck, Andreas; Lendl, Bernhard; Al-Saad, Khalid A; Ali, Mohamed; Celikic, Minja; Ofner, Johannes

2018-02-01

Microspectroscopic techniques are widely used to complement histological studies. Due to recent developments in the field of chemical imaging, combined chemical analysis has become attractive. This technique facilitates a deepened analysis compared to single techniques or side-by-side analysis. In this study, rat brains harvested one week after induction of photothrombotic stroke were investigated. Adjacent thin cuts from rats' brains were imaged using Fourier transform infrared (FT-IR) microspectroscopy and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The LA-ICP-MS data were normalized using an internal standard (a thin gold layer). The acquired hyperspectral data cubes were fused and subjected to multivariate analysis. Brain regions affected by stroke as well as unaffected gray and white matter were identified and classified using a model based on either partial least squares discriminant analysis (PLS-DA) or random decision forest (RDF) algorithms. The RDF algorithm demonstrated the best results for classification. Improved classification was observed in the case of fused data in comparison to individual data sets (either FT-IR or LA-ICP-MS). Variable importance analysis demonstrated that both molecular and elemental content contribute to the improved RDF classification. Univariate spectral analysis identified biochemical properties of the assigned tissue types. Classification of multisensor hyperspectral data sets using an RDF algorithm allows access to a novel and in-depth understanding of biochemical processes and solid chemical allocation of different brain regions.

Multimodality instrument for tissue characterization

Science.gov (United States)

Mah, Robert W. (Inventor); Andrews, Russell J. (Inventor)

2004-01-01

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration. The use of this system will make surgical procedures safer, more accurate, and more efficient. Other applications of this system include the detection, prognosis and treatment of breast cancer, prostate cancer, spinal diseases, and use in general exploratory surgery.

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Science.gov (United States)

Cho, Nam-Hoon; Choi, Heung-Kook

2014-01-01

One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM) and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system. PMID:25371701

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Directory of Open Access Journals (Sweden)

Tae-Yun Kim

2014-01-01

Full Text Available One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system.

Automated classification of cell morphology by coherence-controlled holographic microscopy.

Science.gov (United States)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Perforator chimerism for the reconstruction of complex defects: A new chimeric free flap classification system.

Science.gov (United States)

Kim, Jeong Tae; Kim, Youn Hwan; Ghanem, Ali M

2015-11-01

Complex defects present structural and functional challenges to reconstructive surgeons. When compared to multiple free flaps or staged reconstruction, the use of chimeric flaps to reconstruct such defects have many advantages such as reduced number of operative procedures and donor site morbidity as well as preservation of recipient vessels. With increased popularity of perforator flaps, chimeric flaps' harvest and design has benefited from 'perforator concept' towards more versatile and better reconstruction solutions. This article discusses perforator based chimeric flaps and presents a practice based classification system that incorporates the perforator flap concept into "Perforator Chimerism". The authors analyzed a variety of chimeric patterns used in 31 consecutive cases to present illustrative case series and their new classification system. Accordingly, chimeric flaps are classified into four types. Type I: Classical Chimerism, Type II: Anastomotic Chimerism, Type III: Perforator Chimerism and Type IV Mixed Chimerism. Types I on specific source vessel anatomy whilst Type II requires microvascular anastomosis to create the chimeric reconstructive solution. Type III chimeric flaps utilizes the perforator concept to raise two components of tissues without microvascular anastomosis between them. Type IV chimeric flaps are mixed type flaps comprising any combination of Types I to III. Incorporation of the perforator concept in planning and designing chimeric flaps has allowed safe, effective and aesthetically superior reconstruction of complex defects. The new classification system aids reconstructive surgeons and trainees to understand chimeric flaps design, facilitating effective incorporation of this important reconstructive technique into the armamentarium of the reconstruction toolbox. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

MicroRNAs in the Tumor Biology of Soft Tissue Sarcomas

NARCIS (Netherlands)

C.M.M. Gits (Caroline)

2013-01-01

markdownabstract__Abstract__ Soft tissue sarcomas represent a rare, heterogeneous group of mesenchymal tumors. In sarcomas, histological classification, prediction of clinical behaviour and prognosis, and targeted treatment is often a challenge. A better understanding of the biology of soft

Motor Oil Classification using Color Histograms and Pattern Recognition Techniques.

Science.gov (United States)

Ahmadi, Shiva; Mani-Varnosfaderani, Ahmad; Habibi, Biuck

2018-04-20

Motor oil classification is important for quality control and the identification of oil adulteration. In thiswork, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

Classification, diagnosis, and approach to treatment for angioedema

DEFF Research Database (Denmark)

Cicardi, M; Aberer, W; Banerji, A

2014-01-01

Angioedema is defined as localized and self-limiting edema of the subcutaneous and submucosal tissue, due to a temporary increase in vascular permeability caused by the release of vasoactive mediator(s). When angioedema recurs without significant wheals, the patient should be diagnosed to have...... angioedema as a distinct disease. In the absence of accepted classification, different types of angioedema are not uniquely identified. For this reason, the European Academy of Allergy and Clinical Immunology gave its patronage to a consensus conference aimed at classifying angioedema. Four types of acquired...... and three types of hereditary angioedema were identified as separate forms from the analysis of the literature and were presented in detail at the meeting. Here, we summarize the analysis of the data and the resulting classification of angioedema....

Multispectral Image classification using the theories of neural networks

International Nuclear Information System (INIS)

Ardisasmita, M.S.; Subki, M.I.R.

1997-01-01

Image classification is the one of the important part of digital image analysis. the objective of image classification is to identify and regroup the features occurring in an image into one or several classes in terms of the object. basic to the understanding of multispectral classification is the concept of the spectral response of an object as a function of the electromagnetic radiation and the wavelength of the spectrum. new approaches to classification has been developed to improve the result of analysis, these state-of-the-art classifiers are based upon the theories of neural networks. Neural network classifiers are algorithmes which mimic the computational abilities of the human brain. Artificial neurons are simple emulation's of biological neurons; they take in information from sensors or other artificial neurons, perform very simple operations on this data, and pass the result to other recognize the spectral signature of each image pixel. Neural network image classification has been divided into supervised and unsupervised training procedures. In the supervised approach, examples of each cover type can be located and the computer can compute spectral signatures to categorize all pixels in a digital image into several land cover classes. In supervised classification, spectral signatures are generated by mathematically grouping and it does not require analyst-specified training data. Thus, in the supervised approach we define useful information categories and then examine their spectral reparability; in the unsupervised approach the computer determines spectrally sapable classes and then we define thei information value

Radioactive facilities classification criteria

International Nuclear Information System (INIS)

Briso C, H.A.; Riesle W, J.

1992-01-01

Appropriate classification of radioactive facilities into groups of comparable risk constitutes one of the problems faced by most Regulatory Bodies. Regarding the radiological risk, the main facts to be considered are the radioactive inventory and the processes to which these radionuclides are subjected. Normally, operations are ruled by strict safety procedures. Thus, the total activity of the radionuclides existing in a given facility is the varying feature that defines its risk. In order to rely on a quantitative criterion and, considering that the Annual Limits of Intake are widely accepted references, an index based on these limits, to support decisions related to radioactive facilities, is proposed. (author)

Quality assurance and auditing for tissue banking

International Nuclear Information System (INIS)

Strong, M.; Tayo, E.

1999-01-01

Implementation of quality systems can provide many benefits and have a direct impact on the cost of tissue banking. These benefits are achieved by reducing redundancies, streamlining work processes, reducing and waste, and implementing of a process of continuous monitoring and quality improvement, There have been various models written for the use of quality systems in tissue banking but most can be indexed and correlated with the universal ISO 9000 Quality Management System used world-wide in all types of businesses and services since 1986. These standards contain 20 system elements that define the broad-based quality system. Within these elements are included audited systems. The auditing system includes internal assessment and external assessment. An audit is a planned, independent and documented assessment to determine whether agreed upon requirements are being met. Audits are performed by qualified individuals with knowledge of procedures, regulations and associated standards with the primary intention of improving processes. Internal and external assessments are the primary types of audits performed at the tissue center. Internal assessment is performed by the employees of the organization to determine whether activities and -the results of the activities comply with requirements and procedures. External assessment is carried out by independent examinations performed by an external agency. This presentation will describe procedures for internal quality auditing and results of external assessment of tissue banking in North America, as performed by the American Association of Tissue Banks (AATB). The AATB system for external auditing will be described. Examples will be given of the most common errors found by such auditing assessments and procedures for establishing internal quality auditing

Updating Allergy and/or Hypersensitivity Diagnostic Procedures in the WHO ICD-11 Revision.

Science.gov (United States)

Tanno, Luciana Kase; Calderon, Moises A; Li, James; Casale, Thomas; Demoly, Pascal

2016-01-01

The classification of allergy and/or hypersensitivity conditions for the World Health Organization (WHO) International Classification of Diseases (ICD)-11 provides the appropriate corresponding codes for allergic diseases, assuming that the final diagnosis is correct. This classification should be linked to in vitro and in vivo diagnostic procedures. Considering the impact for our specialty, we decided to review the codification of these procedures into the ICD aiming to have a baseline and to suggest changes and/or submit new proposals. For that, we prepared a list of the relevant allergy and/or hypersensitivity diagnostic procedures that health care professionals are dealing with on a daily basis. This was based on the main current guidelines and selected all possible and relevant corresponding terms from the ICD-10 (2015 version) and the ICD-11 β phase foundation (June 2015 version). More than 90% of very specific and important diagnostic procedures currently used by the allergists' community on a daily basis are missing. We observed that some concepts usually used by the allergist community on a daily basis are not fully recognized by other specialties. The whole scheme and the correspondence in the ICD-10 (2015 version) and ICD-11 foundation (June 2015 version) provided us a big picture of the missing or imprecise terms and how they are scattered in the current ICD-11 framework, allowing us to submit new proposals to increase the visibility of the allergy and/or hypersensitivity conditions and diagnostic procedures. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. All rights reserved.

Benign fatty tumors: classification, clinical course, imaging appearance, and treatment

International Nuclear Information System (INIS)

Bancroft, Laura W.; Kransdorf, Mark J.; Peterson, Jeffrey J.; O'Connor, Mary I.

2006-01-01

Lipoma is the most common soft-tissue tumor, with a wide spectrum of clinical presentations and imaging appearances. Several subtypes are described, ranging from lesions entirely composed of mature adipose tissue to tumors intimately associated with nonadipose tissue, to those composed of brown fat. The imaging appearance of these fatty masses is frequently sufficiently characteristic to allow a specific diagnosis. However, in other cases, although a specific diagnosis is not achievable, a meaningful limited differential diagnosis can be established. The purpose of this manuscript is to review the spectrum of benign fatty tumors highlighting the current classification system, clinical presentation and behavior, spectrum of imaging appearances, and treatment. The imaging review emphasizes computed tomography (CT) scanning and magnetic resonance (MR) imaging, differentiating radiologic features. (orig.)

A New Classification Approach Based on Multiple Classification Rules

OpenAIRE

Zhongmei Zhou

2014-01-01

A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

A texton-based approach for the classification of lung parenchyma in CT images

DEFF Research Database (Denmark)

Gangeh, Mehrdad J.; Sørensen, Lauge; Shaker, Saher B.

2010-01-01

In this paper, a texton-based classification system based on raw pixel representation along with a support vector machine with radial basis function kernel is proposed for the classification of emphysema in computed tomography images of the lung. The proposed approach is tested on 168 annotated...... regions of interest consisting of normal tissue, centrilobular emphysema, and paraseptal emphysema. The results show the superiority of the proposed approach to common techniques in the literature including moments of the histogram of filter responses based on Gaussian derivatives. The performance...

On Predicting lung cancer subtypes using ‘omic’ data from tumor and tumor-adjacent histologically-normal tissue

International Nuclear Information System (INIS)

Pineda, Arturo López; Ogoe, Henry Ato; Balasubramanian, Jeya Balaji; Rangel Escareño, Claudia; Visweswaran, Shyam; Herman, James Gordon; Gopalakrishnan, Vanathi

2016-01-01

Adenocarcinoma (ADC) and squamous cell carcinoma (SCC) are the most prevalent histological types among lung cancers. Distinguishing between these subtypes is critically important because they have different implications for prognosis and treatment. Normally, histopathological analyses are used to distinguish between the two, where the tissue samples are collected based on small endoscopic samples or needle aspirations. However, the lack of cell architecture in these small tissue samples hampers the process of distinguishing between the two subtypes. Molecular profiling can also be used to discriminate between the two lung cancer subtypes, on condition that the biopsy is composed of at least 50 % of tumor cells. However, for some cases, the tissue composition of a biopsy might be a mix of tumor and tumor-adjacent histologically normal tissue (TAHN). When this happens, a new biopsy is required, with associated cost, risks and discomfort to the patient. To avoid this problem, we hypothesize that a computational method can distinguish between lung cancer subtypes given tumor and TAHN tissue. Using publicly available datasets for gene expression and DNA methylation, we applied four classification tasks, depending on the possible combinations of tumor and TAHN tissue. First, we used a feature selector (ReliefF/Limma) to select relevant variables, which were then used to build a simple naïve Bayes classification model. Then, we evaluated the classification performance of our models by measuring the area under the receiver operating characteristic curve (AUC). Finally, we analyzed the relevance of the selected genes using hierarchical clustering and IPA® software for gene functional analysis. All Bayesian models achieved high classification performance (AUC > 0.94), which were confirmed by hierarchical cluster analysis. From the genes selected, 25 (93 %) were found to be related to cancer (19 were associated with ADC or SCC), confirming the biological relevance of our

Free classification of regional dialects of American English

Science.gov (United States)

Clopper, Cynthia G.; Pisoni, David B.

2011-01-01

Recent studies have found that naïve listeners perform poorly in forced-choice dialect categorization tasks. However, the listeners' error patterns in these tasks reveal systematic confusions between phonologically similar dialects. In the present study, a free classification procedure was used to measure the perceptual similarity structure of regional dialect variation in the United States. In two experiments, participants listened to a set of short English sentences produced by male talkers only (Experiment 1) and by male and female talkers (Experiment 2). The listeners were instructed to group the talkers by regional dialect into as many groups as they wanted with as many talkers in each group as they wished. Multidimensional scaling analyses of the data revealed three primary dimensions of perceptual similarity (linguistic markedness, geography, and gender). In addition, a comparison of the results obtained from the free classification task to previous results using the same stimulus materials in six-alternative forced-choice categorization tasks revealed that response biases in the six-alternative task were reduced or eliminated in the free classification task. Thus, the results obtained with the free classification task in the current study provided further evidence that the underlying structure of perceptual dialect category representations reflects important linguistic and sociolinguistic factors. PMID:21423862

Free classification of regional dialects of American English.

Science.gov (United States)

Clopper, Cynthia G; Pisoni, David B

2007-07-01

Recent studies have found that naïve listeners perform poorly in forced-choice dialect categorization tasks. However, the listeners' error patterns in these tasks reveal systematic confusions between phonologically similar dialects. In the present study, a free classification procedure was used to measure the perceptual similarity structure of regional dialect variation in the United States. In two experiments, participants listened to a set of short English sentences produced by male talkers only (Experiment 1) and by male and female talkers (Experiment 2). The listeners were instructed to group the talkers by regional dialect into as many groups as they wanted with as many talkers in each group as they wished. Multidimensional scaling analyses of the data revealed three primary dimensions of perceptual similarity (linguistic markedness, geography, and gender). In addition, a comparison of the results obtained from the free classification task to previous results using the same stimulus materials in six-alternative forced-choice categorization tasks revealed that response biases in the six-alternative task were reduced or eliminated in the free classification task. Thus, the results obtained with the free classification task in the current study provided further evidence that the underlying structure of perceptual dialect category representations reflects important linguistic and sociolinguistic factors.

Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment

Science.gov (United States)

Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

2017-04-01

Historically it has been difficult to create high resolution Digital Elevation Models (DEMs) in land-water transition zones due to shallow water depth and often challenging environmental conditions. This gap of information has been reflected as a "white ribbon" with no data in the land-water transition zone. In recent years, the technology of airborne topobathymetric Light Detection and Ranging (LiDAR) has proven capable of filling out the gap by simultaneously capturing topographic and bathymetric elevation information, using only a single green laser. We collected green LiDAR point cloud data in the Knudedyb tidal inlet system in the Danish Wadden Sea in spring 2014. Creating a DEM from a point cloud requires the general processing steps of data filtering, water surface detection and refraction correction. However, there is no transparent and reproducible method for processing green LiDAR data into a DEM, specifically regarding the procedure of water surface detection and modelling. We developed a step-by-step procedure for creating a DEM from raw green LiDAR point cloud data, including a procedure for making a Digital Water Surface Model (DWSM) (see Andersen et al., 2017). Two different classification analyses were applied to the high resolution DEM: A geomorphometric and a morphological classification, respectively. The classification methods were originally developed for a small test area; but in this work, we have used the classification methods to classify the complete Knudedyb tidal inlet system. References Andersen MS, Gergely Á, Al-Hamdani Z, Steinbacher F, Larsen LR, Ernstsen VB (2017). Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol. Earth Syst. Sci., 21: 43-63, doi:10.5194/hess-21-43-2017. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and

Adaptive partial volume classification of MRI data

International Nuclear Information System (INIS)

Chiverton, John P; Wells, Kevin

2008-01-01

Tomographic biomedical images are commonly affected by an imaging artefact known as the partial volume (PV) effect. The PV effect produces voxels composed of a mixture of tissues in anatomical magnetic resonance imaging (MRI) data resulting in a continuity of these tissue classes. Anatomical MRI data typically consist of a number of contiguous regions of tissues or even contiguous regions of PV voxels. Furthermore discontinuities exist between the boundaries of these contiguous image regions. The work presented here probabilistically models the PV effect using spatial regularization in the form of continuous Markov random fields (MRFs) to classify anatomical MRI brain data, simulated and real. A unique approach is used to adaptively control the amount of spatial regularization imposed by the MRF. Spatially derived image gradient magnitude is used to identify the discontinuities between image regions of contiguous tissue voxels and PV voxels, imposing variable amounts of regularization determined by simulation. Markov chain Monte Carlo (MCMC) is used to simulate the posterior distribution of the probabilistic image model. Promising quantitative results are presented for PV classification of simulated and real MRI data of the human brain.

Complications of minimally invasive cosmetic procedures: Prevention and management

Directory of Open Access Journals (Sweden)

Lauren L Levy

2012-01-01

Full Text Available Over the past decade, facial rejuvenation procedures to circumvent traditional surgery have become increasingly popular. Office-based, minimally invasive procedures can promote a youthful appearance with minimal downtime and low risk of complications. Injectable botulinum toxin (BoNT, soft-tissue fillers, and chemical peels are among the most popular non-invasive rejuvenation procedures, and each has unique applications for improving facial aesthetics. Despite the simplicity and reliability of office-based procedures, complications can occur even with an astute and experienced injector. The goal of any procedure is to perform it properly and safely; thus, early recognition of complications when they do occur is paramount in dictating prevention of long-term sequelae. The most common complications from BoNT and soft-tissue filler injection are bruising, erythema and pain. With chemical peels, it is not uncommon to have erythema, irritation and burning. Fortunately, these side effects are normally transient and have simple remedies. More serious complications include muscle paralysis from BoNT, granuloma formation from soft-tissue filler placement and scarring from chemical peels. Thankfully, these complications are rare and can be avoided with excellent procedure technique, knowledge of facial anatomy, proper patient selection, and appropriate pre- and post-skin care. This article reviews complications of office-based, minimally invasive procedures, with emphasis on prevention and management. Practitioners providing these treatments should be well versed in this subject matter in order to deliver the highest quality care.

Wavelet-based feature extraction applied to small-angle x-ray scattering patterns from breast tissue: a tool for differentiating between tissue types

International Nuclear Information System (INIS)

Falzon, G; Pearson, S; Murison, R; Hall, C; Siu, K; Evans, A; Rogers, K; Lewis, R

2006-01-01

This paper reports on the application of wavelet decomposition to small-angle x-ray scattering (SAXS) patterns from human breast tissue produced by a synchrotron source. The pixel intensities of SAXS patterns of normal, benign and malignant tissue types were transformed into wavelet coefficients. Statistical analysis found significant differences between the wavelet coefficients describing the patterns produced by different tissue types. These differences were then correlated with position in the image and have been linked to the supra-molecular structural changes that occur in breast tissue in the presence of disease. Specifically, results indicate that there are significant differences between healthy and diseased tissues in the wavelet coefficients that describe the peaks produced by the axial d-spacing of collagen. These differences suggest that a useful classification tool could be based upon the spectral information within the axial peaks

Comparison of distal soft-tissue procedures combined with a distal chevron osteotomy for moderate to severe hallux valgus: first web-space versus transarticular approach.

Science.gov (United States)

Park, Yu-Bok; Lee, Keun-Bae; Kim, Sung-Kyu; Seon, Jong-Keun; Lee, Jun-Young

2013-11-06

There are two surgical approaches for distal soft-tissue procedures for the correction of hallux valgus-the dorsal first web-space approach, and the medial transarticular approach. The purpose of this study was to compare the outcomes achieved after use of either of these approaches combined with a distal chevron osteotomy in patients with moderate to severe hallux valgus. One hundred and twenty-two female patients (122 feet) who underwent a distal chevron osteotomy as part of a distal soft-tissue procedure for the treatment of symptomatic unilateral moderate to severe hallux valgus constituted the study cohort. The 122 feet were randomly divided into two groups: namely, a dorsal first web-space approach (group D; sixty feet) and a medial transarticular approach (group M; sixty-two feet). The clinical and radiographic results of the two groups were compared at a mean follow-up time of thirty-eight months. The American Orthopaedic Foot & Ankle Society (AOFAS) hindfoot scale hallux metatarsophalangeal-interphalangeal scores improved from a mean and standard deviation of 55.5 ± 12.8 points preoperatively to 93.5 ± 6.3 points at the final follow-up in group D and from 54.9 ± 12.6 points preoperatively to 93.6 ± 6.2 points at the final follow-up in group M. The mean hallux valgus angle in groups D and M was reduced from 32.2° ± 6.3° and 33.1° ± 8.4° preoperatively to 10.5° ± 5.5° and 9.9° ± 5.5°, respectively, at the time of final follow-up. The mean first intermetatarsal angle in groups D and M was reduced from 15.0° ± 2.8° and 15.3° ± 2.7° preoperatively to 6.5° ± 2.2° and 6.3° ± 2.4°, respectively, at the final follow-up. The clinical and radiographic outcomes were not significantly different between the two groups. The final clinical and radiographic outcomes between the two approaches for distal soft-tissue procedures were comparable and equally successful. Accordingly, the results of this study suggest that the medial transarticular

An approach for leukemia classification based on cooperative game theory.

Science.gov (United States)

Torkaman, Atefeh; Charkari, Nasrollah Moghaddam; Aghaeipour, Mahnaz

2011-01-01

Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Multiple myeloma. Among them, leukemia is a serious malignancy that starts in blood tissues especially the bone marrow, where the blood is made. Researches show, leukemia is one of the common cancers in the world. So, the emphasis on diagnostic techniques and best treatments would be able to provide better prognosis and survival for patients. In this paper, an automatic diagnosis recommender system for classifying leukemia based on cooperative game is presented. Through out this research, we analyze the flow cytometry data toward the classification of leukemia into eight classes. We work on real data set from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO). Generally, the data set contains 400 samples taken from human leukemic bone marrow. This study deals with cooperative game used for classification according to different weights assigned to the markers. The proposed method is versatile as there are no constraints to what the input or output represent. This means that it can be used to classify a population according to their contributions. In other words, it applies equally to other groups of data. The experimental results show the accuracy rate of 93.12%, for classification and compared to decision tree (C4.5) with (90.16%) in accuracy. The result demonstrates that cooperative game is very promising to be used directly for classification of leukemia as a part of Active Medical decision support system for interpretation of flow cytometry readout. This system could assist clinical hematologists to properly recognize different kinds of leukemia by preparing suggestions and this could improve the treatment of leukemic

Effect of substrate choice and tissue type on tissue preparation for spectral histopathology by Raman microspectroscopy.

Science.gov (United States)

Fullwood, Leanne M; Griffiths, Dave; Ashton, Katherine; Dawson, Timothy; Lea, Robert W; Davis, Charles; Bonnier, Franck; Byrne, Hugh J; Baker, Matthew J

2014-01-21

Raman spectroscopy is a non-destructive, non-invasive, rapid and economical technique which has the potential to be an excellent method for the diagnosis of cancer and understanding disease progression through retrospective studies of archived tissue samples. Historically, biobanks are generally comprised of formalin fixed paraffin preserved tissue and as a result these specimens are often used in spectroscopic research. Tissue in this state has to be dewaxed prior to Raman analysis to reduce paraffin contributions in the spectra. However, although the procedures are derived from histopathological clinical practice, the efficacy of the dewaxing procedures that are currently employed is questionable. Ineffective removal of paraffin results in corruption of the spectra and previous experiments have shown that the efficacy can depend on the dewaxing medium and processing time. The aim of this study was to investigate the influence of commonly used spectroscopic substrates (CaF2, Spectrosil quartz and low-E slides) and the influence of different histological tissue types (normal, cancerous and metastatic) on tissue preparation and to assess their use for spectral histopathology. Results show that CaF2 followed by Spectrosil contribute the least to the spectral background. However, both substrates retain paraffin after dewaxing. Low-E substrates, which exhibit the most intense spectral background, do not retain wax and resulting spectra are not affected by paraffin peaks. We also show a disparity in paraffin retention depending upon the histological identity of the tissue with abnormal tissue retaining more paraffin than normal.

Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

Directory of Open Access Journals (Sweden)

Ballester Marcos

2010-08-01

Full Text Available Abstract Background Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Methods Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. Results An SN was detected in 88.2% of cases (75/85 women. Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. Conclusions The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type.

Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

International Nuclear Information System (INIS)

Ballester, Marcos; Koskas, Martin; Coutant, Charles; Chéreau, Elisabeth; Seror, Jeremy; Rouzier, Roman; Daraï, Emile

2010-01-01

Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN) procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. An SN was detected in 88.2% of cases (75/85 women). Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type

Automated Classification of Asteroids into Families at Work

Science.gov (United States)

Knežević, Zoran; Milani, Andrea; Cellino, Alberto; Novaković, Bojan; Spoto, Federica; Paolicchi, Paolo

2014-07-01

We have recently proposed a new approach to the asteroid family classification by combining the classical HCM method with an automated procedure to add newly discovered members to existing families. This approach is specifically intended to cope with ever increasing asteroid data sets, and consists of several steps to segment the problem and handle the very large amount of data in an efficient and accurate manner. We briefly present all these steps and show the results from three subsequent updates making use of only the automated step of attributing the newly numbered asteroids to the known families. We describe the changes of the individual families membership, as well as the evolution of the classification due to the newly added intersections between the families, resolved candidate family mergers, and emergence of the new candidates for the mergers. We thus demonstrate how by the new approach the asteroid family classification becomes stable in general terms (converging towards a permanent list of confirmed families), and in the same time evolving in details (to account for the newly discovered asteroids) at each update.

Training echo state networks for rotation-invariant bone marrow cell classification.

Science.gov (United States)

Kainz, Philipp; Burgsteiner, Harald; Asslaber, Martin; Ahammer, Helmut

2017-01-01

The main principle of diagnostic pathology is the reliable interpretation of individual cells in context of the tissue architecture. Especially a confident examination of bone marrow specimen is dependent on a valid classification of myeloid cells. In this work, we propose a novel rotation-invariant learning scheme for multi-class echo state networks (ESNs), which achieves very high performance in automated bone marrow cell classification. Based on representing static images as temporal sequence of rotations, we show how ESNs robustly recognize cells of arbitrary rotations by taking advantage of their short-term memory capacity. The performance of our approach is compared to a classification random forest that learns rotation-invariance in a conventional way by exhaustively training on multiple rotations of individual samples. The methods were evaluated on a human bone marrow image database consisting of granulopoietic and erythropoietic cells in different maturation stages. Our ESN approach to cell classification does not rely on segmentation of cells or manual feature extraction and can therefore directly be applied to image data.

A standardized procedure for using human corpus cavernosum strips to evaluate drug activity.

Science.gov (United States)

Mirone, V; Sorrentino, R; di Villa Bianca, R; Imbimbo, C; Palmieri, A; Fusco, F; Tajana, G; Cirino, G

2000-01-01

The main problem of using human corpus cavernosum (HCC) tissue to perform bioassay is linked to its limited availability further complicated by the heterogeneous source of the tissues used. Here, we show that gender reassignment is a reliable source of human tissue without major ethical problems. Indeed, the entire corpus cavernosum is obtained from the surgery procedure, which allows creating a standardized procedure to prepare HCC strip. In addition, human tissue, if kept in the fridge in the condition described, does not loose its ability to contract to phenylephrine (PE; alpha agonist), angiotensin II (AG II) and KCl up to 4 days. Furthermore, once contracted with PE, HCC relaxes to acetylcholine (endothelium-dependent mechanism); sodium nitroprusside (endothelium-independent mechanism); cromakalim (CRK), a K(ATP) channel opener; or alprostadil, a synthetic PGE2 (ALPR). In conclusion, we have standardized a procedure that allows the use of HCC strips to evaluate drug activity and/or to study pathophysiological mechanisms with an intact functional human tissue up to 4 days from the surgery procedure.

Development and validation of a microRNA based diagnostic assay for primary tumor site classification of liver core biopsies

DEFF Research Database (Denmark)

Perell, Katharina; Vincent, Martin; Vainer, Ben

2015-01-01

for normal liver tissue contamination. Performance was estimated by cross-validation, followed by independent validation on 55 liver core biopsies with a tumor content as low as 10%. A microRNA classifier developed, using the statistical contamination model, showed an overall classification accuracy of 74...... on classification. MicroRNA profiling was performed using quantitative Real-Time PCR on formalin-fixed paraffin-embedded samples. 278 primary tumors and liver metastases, representing nine primary tumor classes, as well as normal liver samples were used as a training set. A statistical model was applied to adjust.......5% upon independent validation. Two-thirds of the samples were classified with high-confidence, with an accuracy of 92% on high-confidence predictions. A classifier trained without adjusting for liver tissue contamination, showed a classification accuracy of 38.2%. Our results indicate that surrounding...

Biogeographic classification of the Caspian Sea

DEFF Research Database (Denmark)

Fendereski, F.; Vogt, M.; Payne, Mark

2014-01-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information deriv...... confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics....... from space and in-situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions...... in phytoplankton phenology, with differences in the date of bloom initiation, its duration and amplitude between ecoregions. A first qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 27 different species of plankton, fish and benthic invertebrate also...

Real-time simulation of soft tissue deformation and electrocautery procedures in laparoscopic rectal cancer radical surgery.

Science.gov (United States)

Sui, Yuan; Pan, Jun J; Qin, Hong; Liu, Hao; Lu, Yun

2017-12-01

Laparoscopic surgery (LS), also referred to as minimally invasive surgery, is a modern surgical technique which is widely applied. The fulcrum effect makes LS a non-intuitive motor skill with a steep learning curve. A hybrid model of tetrahedrons and a multi-layer triangular mesh are constructed to simulate the deformable behavior of the rectum and surrounding tissues in the Position-Based Dynamics (PBD) framework. A heat-conduction based electric-burn technique is employed to simulate the electrocautery procedure. The simulator has been applied for laparoscopic rectum cancer surgery training. From the experimental results, trainees can operate in real time with high degrees of stability and fidelity. A preliminary study was performed to evaluate the realism and usefulness. This prototype simulator has been tested and verified by colorectal surgeons through a pilot study. They believed both the visual and the haptic performance of the simulation are realistic and helpful to enhance laparoscopic skills. Copyright © 2017 John Wiley & Sons, Ltd.

Biogeographic classification of the Caspian Sea

Science.gov (United States)

Fendereski, F.; Vogt, M.; Payne, M. R.; Lachkar, Z.; Gruber, N.; Salmanmahiny, A.; Hosseini, S. A.

2014-11-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information derived from space and in situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions using the hierarchical agglomerative clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total suspended matter (TSM) and its seasonal variation (DTSM). The classification results reveal a robust separation between the northern and the middle/southern basins as well as a separation of the shallow nearshore waters from those offshore. The observed patterns in ecoregions can be attributed to differences in climate and geochemical factors such as distance from river, water depth and currents. A comparison of the annual and monthly mean Chl a concentrations between the different ecoregions shows significant differences (one-way ANOVA, P qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 25 different species of plankton, fish and benthic invertebrate also confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics.

The biobank for the molecular classification of kidney disease: research translation and precision medicine in nephrology.

Science.gov (United States)

Muruve, Daniel A; Mann, Michelle C; Chapman, Kevin; Wong, Josee F; Ravani, Pietro; Page, Stacey A; Benediktsson, Hallgrimur

2017-07-26

Advances in technology and the ability to interrogate disease pathogenesis using systems biology approaches are exploding. As exemplified by the substantial progress in the personalized diagnosis and treatment of cancer, the application of systems biology to enable precision medicine in other disciplines such as Nephrology is well underway. Infrastructure that permits the integration of clinical data, patient biospecimens and advanced technologies is required for institutions to contribute to, and benefit from research in molecular disease classification and to devise specific and patient-oriented treatments. We describe the establishment of the Biobank for the Molecular Classification of Kidney Disease (BMCKD) at the University of Calgary, Alberta, Canada. The BMCKD consists of a fully equipped wet laboratory, an information technology infrastructure, and a formal operational, ethical and legal framework for banking human biospecimens and storing clinical data. The BMCKD first consolidated a large retrospective cohort of kidney biopsy specimens to create a population-based renal pathology database and tissue inventory of glomerular and other kidney diseases. The BMCKD will continue to prospectively bank all kidney biopsies performed in Southern Alberta. The BMCKD is equipped to perform molecular, clinical and epidemiologic studies in renal pathology. The BMCKD also developed formal biobanking procedures for human specimens such as blood, urine and nucleic acids collected for basic and clinical research studies or for advanced diagnostic technologies in clinical care. The BMCKD is guided by standard operating procedures, an ethics framework and legal agreements with stakeholders that include researchers, data custodians and patients. The design and structure of the BMCKD permits its inclusion in a wide variety of research and clinical activities. The BMCKD is a core multidisciplinary facility that will bridge basic and clinical research and integrate precision

Dose distribution in head and neck during dental x-ray procedures

International Nuclear Information System (INIS)

Mason, E.W.; Goepp, R.A.

1978-01-01

Previous studies, notably by Franklin (Angle Ortho., 43:53-64, 1973), have shown significant exposures during cephalometric dental procedures and ways in which these exposures can be reduced. Skin dose over thyroid tissue has been measured by Alcox (J. Am. Dent. Assoc., 88:568-579, 1974), and others. This study is an expansion of thyroid dose measurements by Block, Goepp, and Mason (Angle Ortho., 47:17-24, 1977). The internal dose distribution in the head and neck area due to cephalometric and panoramic dental x-ray procedures is shown along with the dependence of orbit and thyroid dose on patient positioning. Higher doses can be delivered to deep tissue by panoramic machines since tissue at the axis of rotation is exposed during the entire procedure. (author)

A simple working classification proposed for the latrogenic lesions of teeth and associated structures in the oral cavity.

Science.gov (United States)

Shamim, Thorakkal

2013-09-01

Iatrogenic lesions can affect both hard and soft tissues in the oral cavity, induced by the dentist's activity, manner or therapy. There is no approved simple working classification for the iatrogenic lesions of teeth and associated structures in the oral cavity in the literature. A simple working classification is proposed here for iatrogenic lesions of teeth and associated structures in the oral cavity based on its relation with dental specialities. The dental specialities considered in this classification are conservative dentistry and endodontics, orthodontics, oral and maxillofacial surgery and prosthodontics. This classification will be useful for the dental clinician who is dealing with diseases of oral cavity.

Classification of bone scintigrams in hemodialysis patients

International Nuclear Information System (INIS)

Ishibashi, Kazunari; Miyamae, Tatsuya

1985-01-01

Bone scintigrams from a total of 75 hemodialysis patients using sup(99m)Tc-methylene-diphosphonate (MDP) were classified into two groups; Group I (56 patients) in which the uptake of the radioactivity appeared to be relatively high in the soft tissue and low in the bone, and Group II (19 patients) in which high uptake in the bone and low uptake in the soft tissue were observed. Patients in Group I were further classified into two subgroups; Group I sub(A) (articular type, 21 patients) which was characterized by relatively high uptake into the joint, and Group I sub(B) (reduction type, 35 patients) where uptake was faint in the whole region of the bone. The classification of patients in Group II was also performed; Group II sub(A) (spinal type, 14 patients) where high spinal uptake was observed, and Group II sub(B) (cranio-facial type, 5 patients) where high uptake into the cranio-facial region was observed. The results were compared with 146 subjects with normal bone scintigram in terms of the ratio of bone to soft tissue uptake (B/S ratio) for the cranial bone, jaw bone, lumbar vertebra and femoral bone, and the ratio of epiphysis to diaphysis uptake (E/D ratio) for the femoral bone. The B/S ratio was low in Group I and high in Group II for the bone studied, and the E/D ratio was markedly high in Group I sub(A). Histobiochemical examination indicated that patients in Group I sub(A) and Group II may have osteomalacia and secondary hyperparathyroidism, respectively. It was considered that the visual classification and semiquantitative study as described here were useful for evaluating the pathological condition of renal osteodystrophy. (author)

Classification of bone scintigrams in hemodialysis patients

Energy Technology Data Exchange (ETDEWEB)

Ishibashi, Kazunari; Miyamae, Tatsuya

1985-03-01

Bone scintigrams from a total of 75 hemodialysis patients using /sup 99m/Tc-methylene-diphosphonate (MDP) were classified into two groups; Group I (56 patients) in which the uptake of the radioactivity appeared to be relatively high in the soft tissue and low in the bone, and Group II (19 patients) in which high uptake in the bone and low uptake in the soft tissue were observed. Patients in Group I were further classified into two subgroups; Group I sub(A) (articular type, 21 patients) which was characterized by relatively high uptake into the joint, and Group I sub(B) (reduction type, 35 patients) where uptake was faint in the whole region of the bone. The classification of patients in Group II was also performed; Group II sub(A) (spinal type, 14 patients) where high spinal uptake was observed, and Group II sub(B) (cranio-facial type, 5 patients) where high uptake into the cranio-facial region was observed. The results were compared with 146 subjects with normal bone scintigram in terms of the ratio of bone to soft tissue uptake (B/S ratio) for the cranial bone, jaw bone, lumbar vertebra and femoral bone, and the ratio of epiphysis to diaphysis uptake (E/D ratio) for the femoral bone. The B/S ratio was low in Group I and high in Group II for the bone studied, and the E/D ratio was markedly high in Group I sub(A). Histobiochemical examination indicated that patients in Group I sub(A) and Group II may have osteomalacia and secondary hyperparathyroidism, respectively. It was considered that the visual classification and semiquantitative study as described here were useful for evaluating the pathological condition of renal osteodystrophy.

TU-D-209-06: Head and Neck Tissue Dose From X-Ray Scatter to Physicians Performing Cardiovascular Procedures

Energy Technology Data Exchange (ETDEWEB)

Fetterly, K; Schueler, B; Grams, M [Mayo Clinic, Rochester, MN (United States); Sturchio, G [Mayo Clinic, Jacksonville, FL (United States)

2016-06-15

Purpose: The purpose of this work was to characterize the spatial distribution of scatter radiation to the head and neck of a physician performing an x-ray interventional procedure and assess brain, eye lens, and carotid artery dose. Methods: Radiographic x-ray beams were tuned to match the peak energy (56 to 106 keV) and HVL (3.5 to 6.5 mm Al) of x-ray scatter originating from a patient during a fluoroscopic procedure. The radiographic beam was directed upon a Rando phantom from an inferior-left location to mimic a typical patient-operator geometric relationship. A lead-equivalent protective garment was secured to the phantom. Direct exposure Gafchromic film (XRQA2) was placed between the transverse plane layers of the head and neck region of the phantom and exposed with 4 scatter-equivalent radiographic beams. A 3×3 cm{sup 2} film placed at the left collar of the phantom was used to monitor incident dose in the position of a radiation monitoring badge. The films were converted to 2D dose distribution maps using FilmQA Pro software and an Epson 11000-XL scanner. The 2D dose distributions maps were normalized by the left collar dose and the percent of left collar dose (%LCD) was calculated for select tissues. Results: The dose maps had high dynamic range (10{sub 4}) and spatial detail. Considering all transverse planes and 4 scatter beam qualities, the median %LCD values were: whole brain 8.5%, left brain 13%, right brain 5.4%, left eye lens 67%, right eye lens 25%, left carotid artery 72%, and right carotid artery 28%. Conclusion: Scatter radiation dose to an operator can be simulated using a tuned radiographic beam and used to expose a phantom and Gafchromic film, thereby creating detailed 2D dose distribution maps. This work facilitates individualized estimation of dose to select head and neck tissues based on an operator’s radiation monitoring badge value.

[Definition, etiology, classification and presentation forms].

Science.gov (United States)

Mas Garriga, Xavier

2014-01-01

Osteoarthritis is defined as a degenerative process affecting the joints as a result of mechanical and biological disorders that destabilize the balance between the synthesis and degradation of joint cartilage, stimulating the growth of subchondral bone; chronic synovitis is also present. Currently, the joint is considered as a functional unit that includes distinct tissues, mainly cartilage, the synovial membrane, and subchondral bone, all of which are involved in the pathogenesis of the disease. Distinct risk factors for the development of osteoarthritis have been described: general, unmodifiable risk factors (age, sex, and genetic makeup), general, modifiable risk factors (obesity and hormonal factors) and local risk factors (prior joint anomalies and joint overload). Notable among the main factors related to disease progression are joint alignment defects and generalized osteoarthritis. Several classifications of osteoarthritis have been proposed but none is particularly important for the primary care management of the disease. These classifications include etiological (primary or idiopathic forms and secondary forms) and topographical (typical and atypical localizations) classifications, the Kellgren and Lawrence classification (radiological repercussions) and that of the American College of Rheumatology for osteoarthritis of the hand, hip and knee. The prevalence of knee osteoarthritis is 10.2% in Spain and shows a marked discrepancy between clinical and radiological findings. Hand osteoarthritis, with a prevalence of symptomatic involvement of around 6.2%, has several forms of presentation (nodal osteoarthritis, generalized osteoarthritis, rhizarthrosis, and erosive osteoarthritis). Symptomatic osteoarthritis of the hip affects between 3.5% and 5.6% of persons older than 50 years and has different radiological patterns depending on femoral head migration. Copyright © 2014 Elsevier España, S.L. All rights reserved.

Tissues Use Resident Dendritic Cells and Macrophages to Maintain Homeostasis and to Regain Homeostasis upon Tissue Injury: The Immunoregulatory Role of Changing Tissue Environments

Science.gov (United States)

Lech, Maciej; Gröbmayr, Regina; Weidenbusch, Marc; Anders, Hans-Joachim

2012-01-01

Most tissues harbor resident mononuclear phagocytes, that is, dendritic cells and macrophages. A classification that sufficiently covers their phenotypic heterogeneity and plasticity during homeostasis and disease does not yet exist because cell culture-based phenotypes often do not match those found in vivo. The plasticity of mononuclear phagocytes becomes obvious during dynamic or complex disease processes. Different data interpretation also originates from different conceptual perspectives. An immune-centric view assumes that a particular priming of phagocytes then causes a particular type of pathology in target tissues, conceptually similar to antigen-specific T-cell priming. A tissue-centric view assumes that changing tissue microenvironments shape the phenotypes of their resident and infiltrating mononuclear phagocytes to fulfill the tissue's need to maintain or regain homeostasis. Here we discuss the latter concept, for example, why different organs host different types of mononuclear phagocytes during homeostasis. We further discuss how injuries alter tissue environments and how this primes mononuclear phagocytes to enforce this particular environment, for example, to support host defense and pathogen clearance, to support the resolution of inflammation, to support epithelial and mesenchymal healing, and to support the resolution of fibrosis to the smallest possible scar. Thus, organ- and disease phase-specific microenvironments determine macrophage and dendritic cell heterogeneity in a temporal and spatial manner, which assures their support to maintain and regain homeostasis in whatever condition. Mononuclear phagocytes contributions to tissue pathologies relate to their central roles in orchestrating all stages of host defense and wound healing, which often become maladaptive processes, especially in sterile and/or diffuse tissue injuries. PMID:23251037

Bioactive scaffolds for the controlled formation of complex skeletal tissues

NARCIS (Netherlands)

Hofmann, S.; Garcia-Fuentes, M.; Eberli, D.

2011-01-01

Tissue Engineering may offer new treatment alternatives for organ replacement or repair deteriorated organs. Among the clinical applications of Tissue Engineering are the production of artificial skin for burn patients, tissue engineered trachea, cartilage for knee-replacement procedures, urinary

Comparison of connective tissue graft and guided tissue regeneration in covering root surfaces

Directory of Open Access Journals (Sweden)

LotfazarM.

2002-08-01

Full Text Available There are many researches evaluation different methods for covering the root surface. In the most of these studies, type I and II of Miller treatment had been searched. The purpose of this study was a comparison between connective tissue graft (CTG and guided tissue regeneration (GTR with a collagen membrane in the treatment of gingival recession defects (Miller class III. Six patients, each contributing a pair of Miller class III buccal gingival recessions, were treated. The clinical measurements were obtained at baseline and 1,2,4,6,12,18 months after surgery. Statistical analysis were performed using paired t-test between periods (baseline versus 6 months and baseline versus 18 months within each treatment group and also between treatment groups before treatment and 6, 12 and 18 months after the treatment. The treatments were compared by a triple analysis of variance along the time (treatment, patient, time. Both CTG and GTR with a bioabsorbable membrane demonstrated significant clinical and esthetic improvement for gingival recession coverage. The CTG and GTR procedures had mean root coverage of 55% and 47.5% respectively, in the end of study. The CTG group was statistically better than GTR for recession depth, recession width and keratinized tissue width. Also, passing the time (18 months as a distinct factor of treatment procedures was effective in increasing of clinical attachment level and keratinized tissue width.

Observation versus classification in supervised category learning.

Science.gov (United States)

Levering, Kimery R; Kurtz, Kenneth J

2015-02-01

The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

Residual tumor size and IGCCCG risk classification predict additional vascular procedures in patients with germ cell tumors and residual tumor resection: a multicenter analysis of the German Testicular Cancer Study Group.

Science.gov (United States)

Winter, Christian; Pfister, David; Busch, Jonas; Bingöl, Cigdem; Ranft, Ulrich; Schrader, Mark; Dieckmann, Klaus-Peter; Heidenreich, Axel; Albers, Peter

2012-02-01

Residual tumor resection (RTR) after chemotherapy in patients with advanced germ cell tumors (GCT) is an important part of the multimodal treatment. To provide a complete resection of residual tumor, additional surgical procedures are sometimes necessary. In particular, additional vascular interventions are high-risk procedures that require multidisciplinary planning and adequate resources to optimize outcome. The aim was to identify parameters that predict additional vascular procedures during RTR in GCT patients. A retrospective analysis was performed in 402 GCT patients who underwent 414 RTRs in 9 German Testicular Cancer Study Group (GTCSG) centers. Overall, 339 of 414 RTRs were evaluable with complete perioperative data sets. The RTR database was queried for additional vascular procedures (inferior vena cava [IVC] interventions, aortic prosthesis) and correlated to International Germ Cell Cancer Collaborative Group (IGCCCG) classification and residual tumor volume. In 40 RTRs, major vascular procedures (23 IVC resections with or without prosthesis, 11 partial IVC resections, and 6 aortic prostheses) were performed. In univariate analysis, the necessity of IVC intervention was significantly correlated with IGCCCG (14.1% intermediate/poor vs 4.8% good; p=0.0047) and residual tumor size (3.7% size risk features must initially be identified as high-risk patients for vascular procedures and therefore should be referred to specialized surgical centers with the ad hoc possibility of vascular interventions. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Discriminant analysis of normal and malignant breast tissue based upon INAA investigation of elemental concentration

International Nuclear Information System (INIS)

Kwanhoong Ng; Senghuat Ong; Bradley, D.A.; Laimeng Looi

1997-01-01

Discriminant analysis of six trace element concentrations measured by instrumental neutron activation analysis (INAA) in 26 paired-samples of malignant and histologically normal human breast tissues shows the technique to be a potentially valuable clinical tool for making malignant-normal classification. Nonparametric discriminant analysis is performed for the data obtained. Linear and quadratic discriminant analyses are also carried out for comparison. For this data set a formal analysis shows that the elements which may be useful in distinguishing between malignant and normal tissues are Ca, Rb and Br, providing correct classification for 24 out of 26 normal samples and 22 out of 26 malignant samples. (Author)

A fingerprint classification algorithm based on combination of local and global information

Science.gov (United States)

Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu

2011-12-01

Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.

The fractionation of adipose tissue procedure to obtain stromal vascular fractions for regenerative purposes

NARCIS (Netherlands)

van Dongen, Joris A.; Stevens, Hieronymus P.; Parvizi, Mojtaba; van der Lei, Berend; Harmsen, Martin C.

2016-01-01

Autologous adipose tissue transplantation is clinically used to reduce dermal scarring and to restore volume loss. The therapeutic benefit on tissue damage more likely depends on the stromal vascular fraction of adipose tissue than on the adipocyte fraction. This stromal vascular fraction can be

Improved Management of Part Safety Classification System for Nuclear Power Plant

Energy Technology Data Exchange (ETDEWEB)

Park, Jin Young; Park, Youn Won; Park, Heung Gyu; Park, Hyo Chan [BEES Inc., Daejeon (Korea, Republic of)

2016-10-15

As, in recent years, many quality assurance (QA) related incidents, such as falsely-certified parts and forged documentation, etc., were reported in association with the supply of structures, systems, components and parts to nuclear power plants, a need for a better management of safety classification system was addressed so that it would be based more on the level of parts . Presently, the Korean nuclear power plants do not develop and apply relevant procedures for safety classifications, but rather the safety classes of parts are determined solely based on the experience of equipment designers. So proposed in this paper is a better management plan for safety equipment classification system with an aim to strengthen the quality management for parts. The plan was developed through the analysis of newly introduced technical criteria to be applied to parts of nuclear power plant.

Performing MR-guided biopsies in clinical routine: factors that influence accuracy and procedure time

International Nuclear Information System (INIS)

Hoffmann, Ruediger; Thomas, Christoph; Rempp, Hansjoerg; Schmidt, Diethard; Claussen, Claus D.; Clasen, Stephan; Pereira, Philippe L.

2012-01-01

To assess the accuracy, the duration and factors that influence the duration of MRI-guided liver or soft-tissue biopsies. Nineteen liver biopsies and 19 soft-tissue biopsies performed using 1.5T-MRI guidance were retrospectively analysed. Diagnostic performance and complications were assessed. Intervention time was subdivided into preparation period, puncture period and control period. Correlation between procedure time and target size, skin-to-target-distance, used sequences and interventionalists' experience were analysed. Overall sensitivity, specificity and accuracy were 0.86, 1.0 and 0.92, respectively. Two minor complications occurred. Overall median procedure time was 103.5 min. Liver biopsies lasted longer than soft-tissue biopsies (mean [soft-tissue] : 73.0 min, mean [liver] : 134.1 min, P [liver] = 0.048, P [soft-tissue] = 0.005) was significantly prolonged for longer skin-to-target-distances. Lower numbers of image acquisitions (P [liver] = 0.0007, P [soft-tissue] = 0.0012) and interventionalists' experience reduces the procedure duration significantly (P < 0.05), besides all false-negative results appeared during the first five biopsies of each individual radiologist. The interventionalists' experience, skin-to-target-distances and number of image acquisition influence the procedure time significantly. (orig.)

Classification system for oral submucous fibrosis

Directory of Open Access Journals (Sweden)

Chandramani Bhagvan More

2012-01-01

Full Text Available Oral submucous fibrosis (OSMF is a potentially malignant disorder (PMD and crippling condition of oral mucosa. It is a chronic insidious scarring disease of oral cavity, pharynx and upper digestive tract, characterized by progressive inability to open the mouth due to loss of elasticity and development of vertical fibrous bands in labial and buccal tissues. OSMF is a debilitating but preventable oral disease. It predominantly affects people of Southeast Asia and Indian subcontinent, where chewing of arecanut and its commercial preparation is high. Presence of fibrous bands is the main characteristic feature of OSMF. The present literature review provides the compilation of various classification system based on clinical and/or histopathological features of OSMF from several databases. The advantages and drawbacks of these classifications supersede each other, leading to perplexity. An attempt is made to provide and update the knowledge about this potentially malignant disorder to health care providers in order to help in early detection and treatment, thus reducing the mortality of oral cancer.

Novel design of honeybee-inspired needles for percutaneous procedure.

Science.gov (United States)

Sahlabadi, Mohammad; Hutapea, Parsaoran

2018-04-18

The focus of this paper is to present new designs of innovative bioinspired needles to be used during percutaneous procedures. Insect stingers have been known to easily penetrate soft tissues. Bioinspired needles mimicking the barbs in a honeybee stinger were developed for a smaller insertion force, which can provide a less invasive procedure. Decreasing the insertion force will decrease the tissue deformation, which is essential for more accurate targeting. In this study, some design parameters, in particular, barb shape and geometry (i.e. front angle, back angle, and height) were defined, and their effects on the insertion force were investigated. Three-dimensional printing technology was used to manufacture bioinspired needles. A specially-designed insertion test setup using tissue mimicking polyvinyl chloride (PVC) gels was developed to measure the insertion and extraction forces. The barb design parameters were then experimentally modified through detailed experimental procedures to further reduce the insertion force. Different scales of the barbed needles were designed and used to explore the size-scale effect on the insertion force. To further investigate the efficacy of the proposed needle design in real surgeries, preliminary ex vivo insertion tests into bovine liver tissue were performed. Our results show that the insertion force of the needles in different scales decreased by 21-35% in PVC gel insertion tests, and by 46% in bovine liver tissue insertion tests.

An overview of periodontal regenerative procedures for the general dental practitioner

Directory of Open Access Journals (Sweden)

M. Siaili

2018-01-01

Full Text Available The complete regeneration of the periodontal tissues following periodontal disease remains an unmet challenge, and has presented clinicians with a remarkably difficult clinical challenge to solve given the extensive research in this area and our current understanding of the biology of the periodontal tissues. In particular as clinicians we look for treatments that will improve the predictability of the procedure, improve the magnitude of the effect of treatment, and perhaps most importantly in the long term would extend the indications for treatment beyond the need for single enclosed bony defects to allow for suprabony regeneration, preferably with beneficial effects on the gingival soft tissues. A rapid development in both innovative methods and products for the correction of periodontal deficiencies have been reported during the last three decades. For example, guided tissue regeneration with or without the use of bone supplements has been a well-proven treatment modality for the reconstruction of bony defects prior to the tissue engineering era. Active biomaterials have been subsequently introduced to the periodontal community with supporting dental literature suggesting that certain factors should be taken into consideration when undertaking periodontal regenerative procedures. These factors as well as a number of other translational research issues will need to be addressed, and ultimately it is vital that we do not extrapolate results from pre-clinical and animal studies without conducting extensive randomized clinical trials to substantiate outcomes from these procedures. Whatever the outcomes, the pursuit of regeneration of the periodontal tissues remains a goal worth pursuing for our patients. The aim of the review, therefore is to update clinicians on the recent advances in both materials and techniques in periodontal regenerative procedures and to highlight the importance of both patient factors and the technical aspects of

Tissue discrimination in magnetic resonance imaging of the rotator cuff

International Nuclear Information System (INIS)

Meschino, G J; Comas, D S; González, M A; Ballarin, V L; Capiel, C

2016-01-01

Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients’ health. (paper)

Tissue discrimination in magnetic resonance imaging of the rotator cuff

Science.gov (United States)

Meschino, G. J.; Comas, D. S.; González, M. A.; Capiel, C.; Ballarin, V. L.

2016-04-01

Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients’ health.

Diffuse reflectance spectroscopy for optical soft tissue differentiation as remote feedback control for tissue-specific laser surgery.

Science.gov (United States)

Stelzle, Florian; Tangermann-Gerk, Katja; Adler, Werner; Zam, Azhar; Schmidt, Michael; Douplik, Alexandre; Nkenke, Emeka

2010-04-01

Laser surgery does not provide haptic feedback for operating layer-by-layer and thereby preserving vulnerable anatomical structures like nerve tissue or blood vessels. Diffuse reflectance spectra can facilitate remote optical tissue differentiation. It is the aim of the study to use this technique on soft tissue samples, to set a technological basis for a remote optical feedback system for tissue-specific laser surgery. Diffuse reflectance spectra (wavelength range: 350-650 nm) of ex vivo types of soft tissue (a total of 10,800 spectra) of the midfacial region of domestic pigs were remotely measured under reduced environmental light conditions and analyzed in order to differentiate between skin, mucosa, muscle, subcutaneous fat, and nerve tissue. We performed a principal components (PC) analysis (PCA) to reduce the number of variables. Linear discriminant analysis (LDA) was utilized for classification. For the tissue differentiation, we calculated the specificity and sensitivity by receiver operating characteristic (ROC) analysis and the area under curve (AUC). Six PCs were found to be adequate for tissue differentiation with diffuse reflectance spectra using LDA. All of the types of soft tissue could be differentiated with high specificity and sensitivity. Only the tissue pairs nervous tissue/fatty tissue and nervous tissue/mucosa showed a decline of differentiation due to bio-structural similarity. However, both of these tissue pairs could still be differentiated with a specificity and sensitivity of more than 90%. Analyzing diffuse reflectance spectroscopy with PCA and LDA allows for remote differentiation of biological tissue. Considering the limitations of the ex vivo conditions, the obtained results are promising and set a basis for the further development of a feedback system for tissue-specific laser surgery. (c) 2010 Wiley-Liss, Inc.

SAW Classification Algorithm for Chinese Text Classification

OpenAIRE

Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

2015-01-01

Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

Soft Tissue Tumor Immunohistochemistry Update: Illustrative Examples of Diagnostic Pearls to Avoid Pitfalls.

Science.gov (United States)

Wei, Shi; Henderson-Jackson, Evita; Qian, Xiaohua; Bui, Marilyn M

2017-08-01

- Current 2013 World Health Organization classification of tumors of soft tissue arranges these tumors into 12 groups according to their histogenesis. Tumor behavior is classified as benign, intermediate (locally aggressive), intermediate (rarely metastasizing), and malignant. In our practice, a general approach to reaching a definitive diagnosis of soft tissue tumors is to first evaluate clinicoradiologic, histomorphologic, and cytomorphologic features of the tumor to generate some pertinent differential diagnoses. These include the potential line of histogenesis and whether the tumor is benign or malignant, and low or high grade. Although molecular/genetic testing is increasingly finding its applications in characterizing soft tissue tumors, currently immunohistochemistry still not only plays an indispensable role in defining tumor histogenesis, but also serves as a surrogate for underlining molecular/genetic alterations. Objective- To provide an overview focusing on the current concepts in the classification and diagnosis of soft tissue tumors, incorporating immunohistochemistry. This article uses examples to discuss how to use the traditional and new immunohistochemical markers for the diagnosis of soft tissue tumors. Practical diagnostic pearls, summary tables, and figures are used to show how to avoid diagnostic pitfalls. - Data were obtained from pertinent peer-reviewed English-language literature and the authors' first-hand experience as bone and soft tissue pathologists. - -The ultimate goal for a pathologist is to render a specific diagnosis that provides diagnostic, prognostic, and therapeutic information to guide patient care. Immunohistochemistry is integral to the diagnosis and management of soft tissue tumors.

Classification in context

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

Beta adrenergic receptors in human cavernous tissue

Energy Technology Data Exchange (ETDEWEB)

Dhabuwala, C.B.; Ramakrishna, C.V.; Anderson, G.F.

1985-04-01

Beta adrenergic receptor binding was performed with /sup 125/I iodocyanopindolol on human cavernous tissue membrane fractions from normal tissue and transsexual procedures obtained postoperatively, as well as from postmortem sources. Isotherm binding studies on normal fresh tissues indicated that the receptor density was 9.1 fmoles/mg. with a KD of 23 pM. Tissue stored at room temperature for 4 to 6 hours, then at 4C in saline solution for 19 to 20 hours before freezing showed no significant changes in receptor density or affinity, and provided evidence for the stability of postmortem tissue obtained within the same time period. Beta receptor density of 2 cavernous preparations from transsexual procedures was not significantly different from normal control tissues, and showed that high concentrations of estrogen received by these patients had no effect on beta adrenergic receptor density. Displacement of /sup 125/iodocyanopindolol by 5 beta adrenergic agents demonstrated that 1-propranolol had the greatest affinity followed by ICI 118,551, zinterol, metoprolol and practolol. When the results of these displacement studies were subjected to Scatfit, non- linear regression line analysis, a single binding site was described. Based on the relative potency of the selective beta adrenergic agents it appears that these receptors were of the beta 2 subtype.

China's Classification-Based Forest Management: Procedures, Problems, and Prospects

Science.gov (United States)

Dai, Limin; Zhao, Fuqiang; Shao, Guofan; Zhou, Li; Tang, Lina

2009-06-01

China’s new Classification-Based Forest Management (CFM) is a two-class system, including Commodity Forest (CoF) and Ecological Welfare Forest (EWF) lands, so named according to differences in their distinct functions and services. The purposes of CFM are to improve forestry economic systems, strengthen resource management in a market economy, ease the conflicts between wood demands and public welfare, and meet the diversified needs for forest services in China. The formative process of China’s CFM has involved a series of trials and revisions. China’s central government accelerated the reform of CFM in the year 2000 and completed the final version in 2003. CFM was implemented at the provincial level with the aid of subsidies from the central government. About a quarter of the forestland in China was approved as National EWF lands by the State Forestry Administration in 2006 and 2007. Logging is prohibited on National EWF lands, and their landowners or managers receive subsidies of about 70 RMB (US10) per hectare from the central government. CFM represents a new forestry strategy in China and its implementation inevitably faces challenges in promoting the understanding of forest ecological services, generalizing nationwide criteria for identifying EWF and CoF lands, setting up forest-specific compensation mechanisms for ecological benefits, enhancing the knowledge of administrators and the general public about CFM, and sustaining EWF lands under China’s current forestland tenure system. CFM does, however, offer a viable pathway toward sustainable forest management in China.

Characterization of aerosols produced by surgical procedures

Energy Technology Data Exchange (ETDEWEB)

Yeh, H.C.; Muggenburg, B.A.; Lundgren, D.L.; Guilmette, R.A.; Snipes, M.B.; Jones, R.K. [Inhalation Toxicology Research Institute, Albuquerque, NM (United States); Turner, R.S. [Lovelace Health Systems, Albuquerque, NM (United States)

1994-07-01

In many surgeries, especially orthopedic procedures, power tools such as saws and drills are used. These tools may produce aerosolized blood and other biological material from bone and soft tissues. Surgical lasers and electrocautery tools can also produce aerosols when tissues are vaporized and condensed. Studies have been reported in the literature concerning production of aerosols during surgery, and some of these aerosols may contain infectious material. Garden et al. (1988) reported the presence of papilloma virus DNA in the fumes produced from laser surgery, but the infectivity of the aerosol was not assessed. Moon and Nininger (1989) measured the size distribution and production rate of emissions from laser surgery and found that particles were generally less than 0.5 {mu}m diameter. More recently there has been concern expressed over the production of aerosolized blood during surgical procedures that require power tools. In an in vitro study, the production of an aerosol containing the human immunodeficiency virus (HIV) was reported when power tools were used to cut tissues with blood infected with HIV. Another study measured the size distribution of blood aerosols produced by surgical power tools and found blood-containing particles in a number of size ranges. Health care workers are anxious and concerned about whether surgically produced aerosols are inspirable and can contain viable pathogens such as HIV. Other pathogens such as hepatitis B virus (HBV) are also of concern. The Occupational Safety and Health funded a project at the National Institute for Inhalation Toxicology Research Institute to assess the extent of aerosolization of blood and other tissues during surgical procedures. This document reports details of the experimental and sampling approach, methods, analyses, and results on potential production of blood-associated aerosols from surgical procedures in the laboratory and in the hospital surgical suite.

Feasibility of a novel deformable image registration technique to facilitate classification, targeting, and monitoring of tumor and normal tissue

International Nuclear Information System (INIS)

Brock, Kristy K.; Dawson, Laura A.; Sharpe, Michael B.; Moseley, Douglas J.; Jaffray, David A.

2006-01-01

Purpose: To investigate the feasibility of a biomechanical-based deformable image registration technique for the integration of multimodality imaging, image guided treatment, and response monitoring. Methods and Materials: A multiorgan deformable image registration technique based on finite element modeling (FEM) and surface projection alignment of selected regions of interest with biomechanical material and interface models has been developed. FEM also provides an inherent method for direct tracking specified regions through treatment and follow-up. Results: The technique was demonstrated on 5 liver cancer patients. Differences of up to 1 cm of motion were seen between the diaphragm and the tumor center of mass after deformable image registration of exhale and inhale CT scans. Spatial differences of 5 mm or more were observed for up to 86% of the surface of the defined tumor after deformable image registration of the computed tomography (CT) and magnetic resonance images. Up to 6.8 mm of motion was observed for the tumor after deformable image registration of the CT and cone-beam CT scan after rigid registration of the liver. Deformable registration of the CT to the follow-up CT allowed a more accurate assessment of tumor response. Conclusions: This biomechanical-based deformable image registration technique incorporates classification, targeting, and monitoring of tumor and normal tissue using one methodology

Automated detection of breast cancer in resected specimens with fluorescence lifetime imaging

Science.gov (United States)

Phipps, Jennifer E.; Gorpas, Dimitris; Unger, Jakob; Darrow, Morgan; Bold, Richard J.; Marcu, Laura

2018-01-01

Re-excision rates for breast cancer lumpectomy procedures are currently nearly 25% due to surgeons relying on inaccurate or incomplete methods of evaluating specimen margins. The objective of this study was to determine if cancer could be automatically detected in breast specimens from mastectomy and lumpectomy procedures by a classification algorithm that incorporated parameters derived from fluorescence lifetime imaging (FLIm). This study generated a database of co-registered histologic sections and FLIm data from breast cancer specimens (N  =  20) and a support vector machine (SVM) classification algorithm able to automatically detect cancerous, fibrous, and adipose breast tissue. Classification accuracies were greater than 97% for automated detection of cancerous, fibrous, and adipose tissue from breast cancer specimens. The classification worked equally well for specimens scanned by hand or with a mechanical stage, demonstrating that the system could be used during surgery or on excised specimens. The ability of this technique to simply discriminate between cancerous and normal breast tissue, in particular to distinguish fibrous breast tissue from tumor, which is notoriously challenging for optical techniques, leads to the conclusion that FLIm has great potential to assess breast cancer margins. Identification of positive margins before waiting for complete histologic analysis could significantly reduce breast cancer re-excision rates.

Classification

DEFF Research Database (Denmark)

Hjørland, Birger

2017-01-01

This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

Science.gov (United States)

Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

2018-06-01

There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

Change classification in SAR time series: a functional approach

Science.gov (United States)

Boldt, Markus; Thiele, Antje; Schulz, Karsten; Hinz, Stefan

2017-10-01

Change detection represents a broad field of research in SAR remote sensing, consisting of many different approaches. Besides the simple recognition of change areas, the analysis of type, category or class of the change areas is at least as important for creating a comprehensive result. Conventional strategies for change classification are based on supervised or unsupervised landuse / landcover classifications. The main drawback of such approaches is that the quality of the classification result directly depends on the selection of training and reference data. Additionally, supervised processing methods require an experienced operator who capably selects the training samples. This training step is not necessary when using unsupervised strategies, but nevertheless meaningful reference data must be available for identifying the resulting classes. Consequently, an experienced operator is indispensable. In this study, an innovative concept for the classification of changes in SAR time series data is proposed. Regarding the drawbacks of traditional strategies given above, it copes without using any training data. Moreover, the method can be applied by an operator, who does not have detailed knowledge about the available scenery yet. This knowledge is provided by the algorithm. The final step of the procedure, which main aspect is given by the iterative optimization of an initial class scheme with respect to the categorized change objects, is represented by the classification of these objects to the finally resulting classes. This assignment step is subject of this paper.

Segmentation of Clinical Endoscopic Images Based on the Classification of Topological Vector Features

Directory of Open Access Journals (Sweden)

O. A. Dunaeva

2013-01-01

Full Text Available In this work, we describe a prototype of an automatic segmentation system and annotation of endoscopy images. The used algorithm is based on the classification of vectors of the topological features of the original image. We use the image processing scheme which includes image preprocessing, calculation of vector descriptors defined for every point of the source image and the subsequent classification of descriptors. Image preprocessing includes finding and selecting artifacts and equalizating the image brightness. In this work, we give the detailed algorithm of the construction of topological descriptors and the classifier creating procedure based on mutual sharing the AdaBoost scheme and a naive Bayes classifier. In the final section, we show the results of the classification of real endoscopic images.

Classification of phosphogypsum as a waste material from the aspect of environmental protection

Directory of Open Access Journals (Sweden)

Rajković Miloš B.

2004-01-01

Full Text Available Phosphogypsum is primarily classified as a heavy waste. The classification of phosphogypsum as dangerous waste may be only maintained under the condition that phosphates with the highest content of radio nuclides are used in the production of H3PO4 by the so called "wet procedure" (Morocco, Florida, which, due to the great quantity of present radio nuclides, causes considerable environmental pollution by radon. The classification of phosphogypsum as a separate category of radioactive waste may be conditionally accepted, because phosphogypsum is not a radioactive waste. All the instructions about the collection, documentation and storage of phosphogypsum so far on disposal sites, and possible transport, also due to non-existing legal recommendations must comply with the classification of phosphogypsum as dangerous waste.

Determination of quantitative tissue composition by iterative reconstruction on 3D DECT volumes

Energy Technology Data Exchange (ETDEWEB)

Magnusson, Maria [Linkoeping Univ. (Sweden). Dept. of Electrical Engineering; Linkoeping Univ. (Sweden). Dept. of Medical and Health Sciences, Radiation Physics; Linkoeping Univ. (Sweden). Center for Medical Image Science and Visualization (CMIV); Malusek, Alexandr [Linkoeping Univ. (Sweden). Dept. of Medical and Health Sciences, Radiation Physics; Linkoeping Univ. (Sweden). Center for Medical Image Science and Visualization (CMIV); Nuclear Physics Institute AS CR, Prague (Czech Republic). Dept. of Radiation Dosimetry; Muhammad, Arif [Linkoeping Univ. (Sweden). Dept. of Medical and Health Sciences, Radiation Physics; Carlsson, Gudrun Alm [Linkoeping Univ. (Sweden). Dept. of Medical and Health Sciences, Radiation Physics; Linkoeping Univ. (Sweden). Center for Medical Image Science and Visualization (CMIV)

2011-07-01

Quantitative tissue classification using dual-energy CT has the potential to improve accuracy in radiation therapy dose planning as it provides more information about material composition of scanned objects than the currently used methods based on single-energy CT. One problem that hinders successful application of both single- and dual-energy CT is the presence of beam hardening and scatter artifacts in reconstructed data. Current pre- and post-correction methods used for image reconstruction often bias CT attenuation values and thus limit their applicability for quantitative tissue classification. Here we demonstrate simulation studies with a novel iterative algorithm that decomposes every soft tissue voxel into three base materials: water, protein, and adipose. The results demonstrate that beam hardening artifacts can effectively be removed and accurate estimation of mass fractions of each base material can be achieved. Our iterative algorithm starts with calculating parallel projections on two previously reconstructed DECT volumes reconstructed from fan-beam or helical projections with small conebeam angle. The parallel projections are then used in an iterative loop. Future developments include segmentation of soft and bone tissue and subsequent determination of bone composition. (orig.)

The cranial cartilages of teleosts and their classification.

OpenAIRE

Benjamin, M

1990-01-01

The structure and distribution of cartilages has been studied in 45 species from 24 families. The resulting data have been used as a basis for establishing a new classification. A cartilage is regarded as 'cell-rich' if its cells or their lacunae occupy more than half of the tissue volume. Five classes of cell-rich cartilage are recognised (a) hyaline-cell cartilage (common in the lips of bottom-dwelling cyprinids) and its subtypes fibro/hyaline-cell cartilage, elastic/hyaline-cell cartilage ...

Accurate registration of peri-implant soft tissues to create an optimal emergence profile

Directory of Open Access Journals (Sweden)

Ibraheem Fahad Alshiddi

2015-01-01

Full Text Available One of the challenges in restoring anterior space with implant restoration is maintaining the natural looking of peri-implant area. This case report presents a clinical procedure to create the soft tissue emergence profile for anterior maxillary teeth. A 49-year-old male presented with missing right maxillary lateral incisor. A provisional restoration was inserted 1 week after implant placement. Area of the provisional restoration related to the gingival tissue (transmucosal area was adjusted to create an optimum emergence profile. Two months later, an indirect method was used to accurately transfer the soft peri-implant tissues to the master cast. This clinical technique minimizes surgical procedure and avoids the possibility of soft tissue collapsing that may occur during the impression procedure.

Classification of radioactive self-luminous light sources - approved 1975. NBS Handbook 116

International Nuclear Information System (INIS)

Anon.

1977-01-01

The standard establishes the classification of certain radioactive self-luminous light sources according to radionuclide, type of source, activity, and performance requirements. The objectives are to establish minimum prototype testing requirements for radioactive self-luminous light sources, to promote uniformity of marking such sources, and to establish minimum physical performance for such sources. The standard is primarily directed toward assuring adequate containment of the radioactive material. Testing procedures and classification designations are specified for discoloration, temperature, thermal shock, reduced pressure, impact, vibration, and immersion. A range of test requirements is presented according to intended usage and source activity

75 FR 70112 - Medical Devices; General and Plastic Surgery Devices; Classification of Non-Powered Suction...

Science.gov (United States)

2010-11-17

.... FDA-2010-N-0513] Medical Devices; General and Plastic Surgery Devices; Classification of Non-Powered... risks. Adverse tissue reaction Material degradation Improper function of suction apparatus (e.g., reflux.... Material degradation Section 8. Stability and Shelf Life. [[Page 70113

Computer-aided classification of lesions by means of their kinetic signatures in dynamic contrast-enhanced MR images

Science.gov (United States)

Twellmann, Thorsten; ter Haar Romeny, Bart

2008-03-01

The kinetic characteristics of tissue in dynamic contrast-enhanced magnetic resonance imaging data are an important source of information for the differentiation of benign and malignant lesions. Kinetic curves measured for each lesion voxel allow to infer information about the state of the local tissue. As a whole, they reflect the heterogeneity of the vascular structure within a lesion, an important criterion for the preoperative classification of lesions. Current clinical practice in analysis of tissue kinetics however is mainly based on the evaluation of the "most-suspect curve", which is only related to a small, manually or semi-automatically selected region-of-interest within a lesion and does not reflect any information about tissue heterogeneity. We propose a new method which exploits the full range of kinetic information for the automatic classification of lesions. Instead of breaking down the large amount of kinetic information to a single curve, each lesion is considered as a probability distribution in a space of kinetic features, efficiently represented by its kinetic signature obtained by adaptive vector quantization of the corresponding kinetic curves. Dissimilarity of two signatures can be objectively measured using the Mallows distance, which is a metric defined on probability distributions. The embedding of this metric in a suitable kernel function enables us to employ modern kernel-based machine learning techniques for the classification of signatures. In a study considering 81 breast lesions, the proposed method yielded an A z value of 0.89+/-0.01 for the discrimination of benign and malignant lesions in a nested leave-one-lesion-out evaluation setting.

Classification of operational characteristics of commercial cup-anemometers

Energy Technology Data Exchange (ETDEWEB)

Friis Pedersen, T; Schmidt Paulsen, U [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark)

1999-03-01

The present classification of cup-anemometers is based on a procedure for classification of operational characteristics of cup-anemometers that was proposed at the EWEC `97 conference in Dublin 1997. Three definitions of wind speed are considered. The average longitudinal wind speed (ID), the average horizontal wind speed (2D) and the average vector wind speed (3D). The classification is provided in these terms, and additionally, the turbulence intensities, which are defined from the same wind speed definitions. The commercial cup-anemometers have all been calibrated in wind tunnel for the normal calibrations and angular characteristics. Friction was measured by blywheel testing, where the surrounding temperatures were varied over a wide range. The characteristics of the cup-anemometers have been fitted to the heuristic dynamic model, and the response has been calculated in time domain for prescribed ranges of external operational conditions. The results are presented in ranges of maximum deviations of `measured` average wind speed. For each definition of wind speed and turbulence intensity, the cup-anemometers are ranked according to the most precise instrument. Finally, the most important systematic error sources are commented. (au)

Classification in Astronomy: Past and Present

Science.gov (United States)

Feigelson, Eric

2012-03-01

used today with many refinements by Gerard de Vaucouleurs and others. Supernovae, nearly all of which are found in external galaxies, have a complicated classification scheme:Type I with subtypes Ia, Ib, Ic, Ib/c pec and Type II with subtypes IIb, IIL, IIP, and IIn (Turatto 2003). The classification is based on elemental abundances in optical spectra and on optical light curve shapes. Tadhunter (2009) presents a three-dimensional classification of active galactic nuclei involving radio power, emission line width, and nuclear luminosity. These taxonomies have played enormously important roles in the development of astronomy, yet all were developed using heuristic methods. Many are based on qualitative and subjective assessments of spatial, temporal, or spectral properties. A qualitative, morphological approach to astronomical studies was explicitly promoted by Zwicky (1957). Other classifications are based on quantitative criteria, but these criteria were developed by subjective examination of training datasets. For example, starburst galaxies are discriminated from narrow-line Seyfert galaxies by a curved line in a diagramof the ratios of four emission lines (Veilleux and Osterbrock 1987). Class II young stellar objects have been defined by a rectangular region in a mid-infrared color-color diagram (Allen et al. 2004). Short and hard gamma-ray bursts are discriminated by a dip in the distribution of burst durations (Kouveliotou et al. 2000). In no case was a statistical or algorithmic procedure used to define the classes.

Measurement of the hyperelastic properties of 44 pathological ex vivo breast tissue samples

International Nuclear Information System (INIS)

O'Hagan, Joseph J; Samani, Abbas

2009-01-01

The elastic and hyperelastic properties of biological soft tissues have been of interest to the medical community. There are several biomedical applications where parameters characterizing such properties are critical for a reliable clinical outcome. These applications include surgery planning, needle biopsy and brachtherapy where tissue biomechanical modeling is involved. Another important application is interpreting nonlinear elastography images. While there has been considerable research on the measurement of the linear elastic modulus of small tissue samples, little research has been conducted for measuring parameters that characterize the nonlinear elasticity of tissues included in tissue slice specimens. This work presents hyperelastic measurement results of 44 pathological ex vivo breast tissue samples. For each sample, five hyperelastic models have been used, including the Yeoh, N = 2 polynomial, N = 1 Ogden, Arruda-Boyce, and Veronda-Westmann models. Results show that the Yeoh, polynomial and Ogden models are the most accurate in terms of fitting experimental data. The results indicate that almost all of the parameters corresponding to the pathological tissues are between two times to over two orders of magnitude larger than those of normal tissues, with C 11 showing the most significant difference. Furthermore, statistical analysis indicates that C 02 of the Yeoh model, and C 11 and C 20 of the polynomial model have very good potential for cancer classification as they show statistically significant differences for various cancer types, especially for invasive lobular carcinoma. In addition to the potential for use in cancer classification, the presented data are very important for applications such as surgery planning and virtual reality based clinician training systems where accurate nonlinear tissue response modeling is required.

Measurement of the hyperelastic properties of 44 pathological ex vivo breast tissue samples

Energy Technology Data Exchange (ETDEWEB)

O' Hagan, Joseph J; Samani, Abbas [Department of Electrical and Computer Engineering, University of Western Ontario, London, ON (Canada)], E-mail: asamani@uwo.ca

2009-04-21

The elastic and hyperelastic properties of biological soft tissues have been of interest to the medical community. There are several biomedical applications where parameters characterizing such properties are critical for a reliable clinical outcome. These applications include surgery planning, needle biopsy and brachtherapy where tissue biomechanical modeling is involved. Another important application is interpreting nonlinear elastography images. While there has been considerable research on the measurement of the linear elastic modulus of small tissue samples, little research has been conducted for measuring parameters that characterize the nonlinear elasticity of tissues included in tissue slice specimens. This work presents hyperelastic measurement results of 44 pathological ex vivo breast tissue samples. For each sample, five hyperelastic models have been used, including the Yeoh, N = 2 polynomial, N = 1 Ogden, Arruda-Boyce, and Veronda-Westmann models. Results show that the Yeoh, polynomial and Ogden models are the most accurate in terms of fitting experimental data. The results indicate that almost all of the parameters corresponding to the pathological tissues are between two times to over two orders of magnitude larger than those of normal tissues, with C{sub 11} showing the most significant difference. Furthermore, statistical analysis indicates that C{sub 02} of the Yeoh model, and C{sub 11} and C{sub 20} of the polynomial model have very good potential for cancer classification as they show statistically significant differences for various cancer types, especially for invasive lobular carcinoma. In addition to the potential for use in cancer classification, the presented data are very important for applications such as surgery planning and virtual reality based clinician training systems where accurate nonlinear tissue response modeling is required.

Measurement of the hyperelastic properties of 44 pathological ex vivo breast tissue samples

Science.gov (United States)

O'Hagan, Joseph J.; Samani, Abbas

2009-04-01

The elastic and hyperelastic properties of biological soft tissues have been of interest to the medical community. There are several biomedical applications where parameters characterizing such properties are critical for a reliable clinical outcome. These applications include surgery planning, needle biopsy and brachtherapy where tissue biomechanical modeling is involved. Another important application is interpreting nonlinear elastography images. While there has been considerable research on the measurement of the linear elastic modulus of small tissue samples, little research has been conducted for measuring parameters that characterize the nonlinear elasticity of tissues included in tissue slice specimens. This work presents hyperelastic measurement results of 44 pathological ex vivo breast tissue samples. For each sample, five hyperelastic models have been used, including the Yeoh, N = 2 polynomial, N = 1 Ogden, Arruda-Boyce, and Veronda-Westmann models. Results show that the Yeoh, polynomial and Ogden models are the most accurate in terms of fitting experimental data. The results indicate that almost all of the parameters corresponding to the pathological tissues are between two times to over two orders of magnitude larger than those of normal tissues, with C11 showing the most significant difference. Furthermore, statistical analysis indicates that C02 of the Yeoh model, and C11 and C20 of the polynomial model have very good potential for cancer classification as they show statistically significant differences for various cancer types, especially for invasive lobular carcinoma. In addition to the potential for use in cancer classification, the presented data are very important for applications such as surgery planning and virtual reality based clinician training systems where accurate nonlinear tissue response modeling is required.

Using cell nuclei features to detect colon cancer tissue in hematoxylin and eosin stained slides.

Science.gov (United States)

Jørgensen, Alex Skovsbo; Rasmussen, Anders Munk; Andersen, Niels Kristian Mäkinen; Andersen, Simon Kragh; Emborg, Jonas; Røge, Rasmus; Østergaard, Lasse Riis

2017-08-01

Currently, diagnosis of colon cancer is based on manual examination of histopathological images by a pathologist. This can be time consuming and interpretation of the images is subject to inter- and intra-observer variability. This may be improved by introducing a computer-aided diagnosis (CAD) system for automatic detection of cancer tissue within whole slide hematoxylin and eosin (H&E) stains. Cancer disrupts the normal control mechanisms of cell proliferation and differentiation, affecting the structure and appearance of the cells. Therefore, extracting features from segmented cell nuclei structures may provide useful information to detect cancer tissue. A framework for automatic classification of regions of interest (ROI) containing either benign or cancerous colon tissue extracted from whole slide H&E stained images using cell nuclei features was proposed. A total of 1,596 ROI's were extracted from 87 whole slide H&E stains (44 benign and 43 cancer). A cell nuclei segmentation algorithm consisting of color deconvolution, k-means clustering, local adaptive thresholding, and cell separation was performed within the ROI's to extract cell nuclei features. From the segmented cell nuclei structures a total of 750 texture and intensity-based features were extracted for classification of the ROI's. The nine most discriminative cell nuclei features were used in a random forest classifier to determine if the ROI's contained benign or cancer tissue. The ROI classification obtained an area under the curve (AUC) of 0.96, sensitivity of 0.88, specificity of 0.92, and accuracy of 0.91 using an optimized threshold. The developed framework showed promising results in using cell nuclei features to classify ROIs into containing benign or cancer tissue in H&E stained tissue samples. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

International Nuclear Information System (INIS)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

2013-01-01

The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory. (paper)

Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

Science.gov (United States)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

2013-03-01

The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

[Guideline development for rehabilitation of breast cancer patients - phase 2: findings from the classification of therapeutic procedures, KTL-data-analysis].

Science.gov (United States)

Domann, U; Brüggemann, S; Klosterhuis, H; Weis, J

2007-08-01

Aim of this project is the development of an evidence based guideline for the rehabilitation of breast cancer patients, funded by the German Pension Insurance scheme. The project consists of four phases. This paper is focused on the 2nd phase, i.e., analysis of procedures in rehabilitation based on evidence based therapeutic modules. As a result of a systematic literature review 14 therapeutic modules were defined. From a total of 840 possible KTL Codes (Klassifikation Therapeutischer Leistungen, Classification of therapeutic procedures), 229 could be assigned to these modules. These analyses are based on 24685 patients in 57 rehabilitation clinics, who had been treated in 2003. For these modules the number of patients having received those interventions as well as the duration of the modules were calculated. The data were analysed with respect to the influence of age and comorbidity. Moreover, differences between rehabilitation clinics were investigated according to the category of interventions. Our findings show great variability in the use of the therapeutic modules. Therapeutic modules like Physiotherapy (91.6%), Training Therapy (85.2%) and Information (97.8%) are provided to most of the patients. Younger patients receive more treatments than older patients, and patients with higher comorbidity receive more Physiotherapie, Lymphoedema Therapy and Psychological Interventions than patients without comorbidities. Data analysis shows wide interindividual variability with regard to the therapeutic modules. This variability is related to age and comorbidity of the patients. Furthermore, great differences were found between the rehabilitation clinics concerning the use of the various interventions. This variability supports the necessity of developing and implementing an evidence based guideline for the rehabilitation of breast cancer patients. The next step will be discussing these findings with experts from science and clinical practice.

Texture analysis of speckle in optical coherence tomography images of tissue phantoms

International Nuclear Information System (INIS)

Gossage, Kirk W; Smith, Cynthia M; Kanter, Elizabeth M; Hariri, Lida P; Stone, Alice L; Rodriguez, Jeffrey J; Williams, Stuart K; Barton, Jennifer K

2006-01-01

Optical coherence tomography (OCT) is an imaging modality capable of acquiring cross-sectional images of tissue using back-reflected light. Conventional OCT images have a resolution of 10-15 μm, and are thus best suited for visualizing tissue layers and structures. OCT images of collagen (with and without endothelial cells) have no resolvable features and may appear to simply show an exponential decrease in intensity with depth. However, examination of these images reveals that they display a characteristic repetitive structure due to speckle.The purpose of this study is to evaluate the application of statistical and spectral texture analysis techniques for differentiating living and non-living tissue phantoms containing various sizes and distributions of scatterers based on speckle content in OCT images. Statistically significant differences between texture parameters and excellent classification rates were obtained when comparing various endothelial cell concentrations ranging from 0 cells/ml to 25 million cells/ml. Statistically significant results and excellent classification rates were also obtained using various sizes of microspheres with concentrations ranging from 0 microspheres/ml to 500 million microspheres/ml. This study has shown that texture analysis of OCT images may be capable of differentiating tissue phantoms containing various sizes and distributions of scatterers

Classification of refrigerants; Classification des fluides frigorigenes

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

Bio-geographic classification of the Caspian Sea

Science.gov (United States)

Fendereski, F.; Vogt, M.; Payne, M. R.; Lachkar, Z.; Gruber, N.; Salmanmahiny, A.; Hosseini, S. A.

2014-03-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information derived from space and in-situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions using the Hierarchical Agglomerative Clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total suspended matter (TSM) and its seasonal variation (DTSM). The classification results reveal a robust separation between the northern and the middle/southern basins as well as a separation of the shallow near-shore waters from those off-shore. The observed patterns in ecoregions can be attributed to differences in climate and geochemical factors such as distance from river, water depth and currents. A comparison of the annual and monthly mean Chl a concentrations between the different ecoregions shows significant differences (Kruskal-Wallis rank test, P qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 27 different species of plankton, fish and benthic invertebrate also confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics.

Deterministic effects of interventional radiology procedures

International Nuclear Information System (INIS)

Shope, Thomas B.

1997-01-01

The purpose of this paper is to describe deterministic radiation injuries reported to the Food and Drug Administration (FDA) that resulted from therapeutic, interventional procedures performed under fluoroscopic guidance, and to investigate the procedure or equipment-related factors that may have contributed to the injury. Reports submitted to the FDA under both mandatory and voluntary reporting requirements which described radiation-induced skin injuries from fluoroscopy were investigated. Serious skin injuries, including moist desquamation and tissues necrosis, have occurred since 1992. These injuries have resulted from a variety of interventional procedures which have required extended periods of fluoroscopy compared to typical diagnostic procedures. Facilities conducting therapeutic interventional procedures need to be aware of the potential for patient radiation injury and take appropriate steps to limit the potential for injury. (author)

A Study on the Systematization of Classification Process for NSG Trigger List Items

Energy Technology Data Exchange (ETDEWEB)

Yang, Seunghyo; Tae, Jaewoong; Shin, Donghoon [Korea Institute of Nuclear Nonproliferation and Control/Nuclear Export Control Div., Daejeon (Korea, Republic of)

2013-05-15

In 1978, Nuclear Suppliers Group (NSG) was established to prevent nuclear items from being used for nuclear weapons. NSG drew up the NSG Guidelines (INFCIRC/254) that regulates export control items(so-called NSG trigger list items) and procedures. NSG recommends its member countries to reflect these guidelines on their export control systems and fulfill their obligations. Korea has carried out export controls on nuclear items by reflecting NSG Guidelines on Notice on Trade of Strategic Item of Foreign Trade Act since joining NSG in 1995. Nuclear export control starts with Classification that determines whether export items can be used for strategic items (goods and technologies that can be exclusively used for the manufacture, development and use of WMD). The standard of Classification is based on the NSG Guidelines. However, due to the qualitative characteristics of the Guidelines, there take place lots of difficulties in the Classification. Thus this study aims to suggest the systematic Classification process. Recently, the number of Classification requests is rapidly increasing due to the UAE commercial nuclear power plants and the Jordan reactors export. It is required to provide a more systematic Classification standard and process in order to provide an efficient and consistent Classification. Thus, this study analyzed limitations of EDP which causes difficulties in the process of classification due to its qualitative characteristics. Besides, it established systematic Classification process by quantitatively analyzing EDP. Consequently, it is expected that the results of this study will be used for as actual Classification. It still remains to establish a criterion of detailed information, which is one of the most important in the Classification for technology. Therefore, a further study will be conducted to establish a criterion of detailed information by analyzing Classification cases through the text mining techniques.

A Study on the Systematization of Classification Process for NSG Trigger List Items

International Nuclear Information System (INIS)

Yang, Seunghyo; Tae, Jaewoong; Shin, Donghoon

2013-01-01

In 1978, Nuclear Suppliers Group (NSG) was established to prevent nuclear items from being used for nuclear weapons. NSG drew up the NSG Guidelines (INFCIRC/254) that regulates export control items(so-called NSG trigger list items) and procedures. NSG recommends its member countries to reflect these guidelines on their export control systems and fulfill their obligations. Korea has carried out export controls on nuclear items by reflecting NSG Guidelines on Notice on Trade of Strategic Item of Foreign Trade Act since joining NSG in 1995. Nuclear export control starts with Classification that determines whether export items can be used for strategic items (goods and technologies that can be exclusively used for the manufacture, development and use of WMD). The standard of Classification is based on the NSG Guidelines. However, due to the qualitative characteristics of the Guidelines, there take place lots of difficulties in the Classification. Thus this study aims to suggest the systematic Classification process. Recently, the number of Classification requests is rapidly increasing due to the UAE commercial nuclear power plants and the Jordan reactors export. It is required to provide a more systematic Classification standard and process in order to provide an efficient and consistent Classification. Thus, this study analyzed limitations of EDP which causes difficulties in the process of classification due to its qualitative characteristics. Besides, it established systematic Classification process by quantitatively analyzing EDP. Consequently, it is expected that the results of this study will be used for as actual Classification. It still remains to establish a criterion of detailed information, which is one of the most important in the Classification for technology. Therefore, a further study will be conducted to establish a criterion of detailed information by analyzing Classification cases through the text mining techniques

A review of the regenerative endodontic treatment procedure

Directory of Open Access Journals (Sweden)

Bin-Na Lee,

2015-08-01

Full Text Available Traditionally, apexification has been used to treat immature permanent teeth that have lost pulp vitality. This technique promotes the formation of an apical barrier to close the open apex so that the filling materials can be confined to the root canal. Because tissue regeneration cannot be achieved with apexification, a new technique called regenerative endodontic treatment was presented recently to treat immature permanent teeth. Regenerative endodontic treatment is a treatment procedure designed to replace damaged pulp tissue with viable tissue which restores the normal function of the pulp-dentin structure. After regenerative endodontic treatment, continued root development and hard tissue deposition on the dentinal wall can occur under ideal circumstances. However, it is difficult to predict the result of regenerative endodontic treatment. Therefore, the purpose of this study was to summarize multiple factors effects on the result of regenerative endodontic treatment in order to achieve more predictable results. In this study, we investigated the features of regenerative endodontic treatment in comparison with those of other pulp treatment procedures and analyzed the factors that have an effect on regenerative endodontic treatment.

Classification of hydration status using electrocardiogram and machine learning

Science.gov (United States)

Kaveh, Anthony; Chung, Wayne

2013-10-01

The electrocardiogram (ECG) has been used extensively in clinical practice for decades to non-invasively characterize the health of heart tissue; however, these techniques are limited to time domain features. We propose a machine classification system using support vector machines (SVM) that uses temporal and spectral information to classify health state beyond cardiac arrhythmias. Our method uses single lead ECG to classify volume depletion (or dehydration) without the lengthy and costly blood analysis tests traditionally used for detecting dehydration status. Our method builds on established clinical ECG criteria for identifying electrolyte imbalances and lends to automated, computationally efficient implementation. The method was tested on the MIT-BIH PhysioNet database to validate this purely computational method for expedient disease-state classification. The results show high sensitivity, supporting use as a cost- and time-effective screening tool.

Detection of Chlamydia in postmortal formalin-fixed tissue

DEFF Research Database (Denmark)

Lundemose, AG; Lundemose, JB; Birkelund, Svend

1989-01-01

A procedure to detect Chlamydia in postmortal formalin-fixed tissue is described. Monoclonal antibodies against a genus specific chlamydia epitope were used in immunofluorescence to detect chlamydia inclusions in formalin-fixed tissue sections. Lung sections from chlamydia-infected mice were....... Background and non-specific fluorescence were reduced by treating the tissue sections with trypsin, rabbit serum and Evans blue counterstain. Besides giving an exact diagnosis at autopsy, the method provides the possibility of determining the occurrence of chlamydia infections in various tissues, based...

Development of an ICF-based eligibility procedure for education in Switzerland.

Science.gov (United States)

Hollenweger, Judith

2011-05-31

Starting in January 2011, Switzerland will implement a multidimensional, context-sensitive procedure to establish eligibility in education systems. This paper provides a brief overview of the different eligibility-related practices with a special focus on children with disabilities. The paper then outlines the philosophical and conceptual framework of the eligibility procedure based on the International Classification of Functioning, Disability and Health, and the UN Convention on the Rights of Persons with Disability. The different components and methodology applied to organise information in the process towards establishing eligibility are also presented. Finally, some observations are made regarding transparent and just applications of the eligibility procedure, and the implementation of this new eligibility procedure.

Non-Hodgkin lymphoma response evaluation with MRI texture classification

Directory of Open Access Journals (Sweden)

Heinonen Tomi T

2009-06-01

Full Text Available Abstract Background To show magnetic resonance imaging (MRI texture appearance change in non-Hodgkin lymphoma (NHL during treatment with response controlled by quantitative volume analysis. Methods A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests. Results NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images. Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue. Conclusion Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.

An Approach for Leukemia Classification Based on Cooperative Game Theory

Directory of Open Access Journals (Sweden)

Atefeh Torkaman

2011-01-01

Full Text Available Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Multiple myeloma. Among them, leukemia is a serious malignancy that starts in blood tissues especially the bone marrow, where the blood is made. Researches show, leukemia is one of the common cancers in the world. So, the emphasis on diagnostic techniques and best treatments would be able to provide better prognosis and survival for patients. In this paper, an automatic diagnosis recommender system for classifying leukemia based on cooperative game is presented. Through out this research, we analyze the flow cytometry data toward the classification of leukemia into eight classes. We work on real data set from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO. Generally, the data set contains 400 samples taken from human leukemic bone marrow. This study deals with cooperative game used for classification according to different weights assigned to the markers. The proposed method is versatile as there are no constraints to what the input or output represent. This means that it can be used to classify a population according to their contributions. In other words, it applies equally to other groups of data. The experimental results show the accuracy rate of 93.12%, for classification and compared to decision tree (C4.5 with (90.16% in accuracy. The result demonstrates that cooperative game is very promising to be used directly for classification of leukemia as a part of Active Medical decision support system for interpretation of flow cytometry readout. This system could assist clinical hematologists to properly recognize different kinds of leukemia by preparing suggestions and this could improve the treatment

Internationally Comparable Measures of Occupational Status for the 1988 International Standard Classification of Occupations

NARCIS (Netherlands)

Ganzeboom, H.B.G.; Treiman, D.J.

1996-01-01

This paper provides operational procedures for coding internationally comparable measures of occupational status from the recently published International Standard Classification of Occupation 1988 (ISCO88) of the International Labor Office (ILO, 1990). We first discuss the nature of the ISCO88

Unclassified sarcomas : a study to improve classification in a cohort of Golden Retriever dogs

NARCIS (Netherlands)

Boerkamp, Kim M; Hellmén, Eva; Willén, Helena; Grinwis, Guy C M; Teske, Erik; Rutteman, Gerard R

2016-01-01

Morphologically, canine soft-tissue sarcomas (STSs) resemble human STSs. In humans, proper classification of STSs is considered essential to improve insight in the biology of these tumors, and to optimize diagnosis and therapy. To date, there is a paucity of data published on the significance of

Differentiation of osteophyte types in osteoarthritis - proposal of a histological classification.

Science.gov (United States)

Junker, Susann; Krumbholz, Grit; Frommer, Klaus W; Rehart, Stefan; Steinmeyer, Jürgen; Rickert, Markus; Schett, Georg; Müller-Ladner, Ulf; Neumann, Elena

2016-01-01

Osteoarthritis is not only characterized by cartilage degradation but also involves subchondral bone remodeling and osteophyte formation. Osteophytes are fibrocartilage-capped bony outgrowths originating from the periosteum. The pathophysiology of osteophyte formation is not completely understood. Yet, different research approaches are under way. Therefore, a histological osteophyte classification to achieve comparable results in osteophyte research was established for application to basic science research questions. The osteophytes were collected from knee joints of osteoarthritis patients (n=10, 94 osteophytes in total) after joint replacement surgery. Their size and origin in the respective joint were photo-documented. To develop an osteophyte classification, serial tissue sections were evaluated using histological (hematoxylin and eosin, Masson's trichrome, toluidine blue) and immunohistochemical staining (collagen type II). Based on the histological and immunohistochemical evaluation, osteophytes were categorized into four different types depending on the degree of ossification and the percentage of mesenchymal connective tissue. Size and localization of osteophytes were independent from the histological stages. This histological classification system of osteoarthritis osteophytes provides a helpful tool for analyzing and monitoring osteophyte development and for characterizing osteophyte types within a single human joint and may therefore contribute to achieve comparable results when analyzing histological findings in osteophytes. Copyright © 2015 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

Soft-tissue tension total knee arthroplasty.

Science.gov (United States)

Asano, Hiroshi; Hoshino, Akiho; Wilton, Tim J

2004-08-01

It is far from clear how best to define the proper strength of soft-tissue tensioning in total knee arthroplasty (TKA). We attached a torque driver to the Monogram balancer/tensor device and measured soft-tissue tension in full extension and 90 degrees flexion during TKA. In our surgical procedure, when we felt proper soft-tissue tension was being applied, the mean distraction force was noted to be 126N in extension and 121N in flexion. There was no significant correlation between soft-tissue tension and the postoperative flexion angle finally achieved. To the best of our knowledge, this is the first study to assess the actual distraction forces in relation to soft-tissue tension in TKA. Further study may reveal the most appropriate forces to achieve proper soft-tissue tension in the wide variety of circumstances presenting at knee arthroplasty.

New casemix classification as an alternative method for budget allocation in thai oral healthcare service: a pilot study.

Science.gov (United States)

Wisaijohn, Thunthita; Pimkhaokham, Atiphan; Lapying, Phenkhae; Itthichaisri, Chumpot; Pannarunothai, Supasit; Igarashi, Isao; Kawabuchi, Koichi

2010-01-01

This study aimed to develop a new casemix classification system as an alternative method for the budget allocation of oral healthcare service (OHCS). Initially, the International Statistical of Diseases and Related Health Problem, 10th revision, Thai Modification (ICD-10-TM) related to OHCS was used for developing the software "Grouper". This model was designed to allow the translation of dental procedures into eight-digit codes. Multiple regression analysis was used to analyze the relationship between the factors used for developing the model and the resource consumption. Furthermore, the coefficient of variance, reduction in variance, and relative weight (RW) were applied to test the validity. The results demonstrated that 1,624 OHCS classifications, according to the diagnoses and the procedures performed, showed high homogeneity within groups and heterogeneity between groups. Moreover, the RW of the OHCS could be used to predict and control the production costs. In conclusion, this new OHCS casemix classification has a potential use in a global decision making.

New Casemix Classification as an Alternative Method for Budget Allocation in Thai Oral Healthcare Service: A Pilot Study

Directory of Open Access Journals (Sweden)

Thunthita Wisaijohn

2010-01-01

Full Text Available This study aimed to develop a new casemix classification system as an alternative method for the budget allocation of oral healthcare service (OHCS. Initially, the International Statistical of Diseases and Related Health Problem, 10th revision, Thai Modification (ICD-10-TM related to OHCS was used for developing the software “Grouper”. This model was designed to allow the translation of dental procedures into eight-digit codes. Multiple regression analysis was used to analyze the relationship between the factors used for developing the model and the resource consumption. Furthermore, the coefficient of variance, reduction in variance, and relative weight (RW were applied to test the validity. The results demonstrated that 1,624 OHCS classifications, according to the diagnoses and the procedures performed, showed high homogeneity within groups and heterogeneity between groups. Moreover, the RW of the OHCS could be used to predict and control the production costs. In conclusion, this new OHCS casemix classification has a potential use in a global decision making.

Modality and risk management for orthodontic extrusion procedures in interdisciplinary treatment for generating proper bone and tissue contours for the planned implant: a case report.

Science.gov (United States)

Maeda, Sachiko; Sasaki, Takeshi

2015-12-01

In adult interdisciplinary treatments with using dental implants, limited orthodontic treatment, especially orthodontic extrusion (OE), offers many benefits by both correcting teeth alignment and by contributing to the regeneration of periodontal tissues. However, orthodontic procedures carry some risks and unpredictabilities that might compromise tooth and/or periodontal tissue health. Especially in complex cases, it is difficult to decide which orthodontic treatment modalities should be combined, in what sequences they should be applied, and what their force systems and treatment times are.To achieve optimum results, some cases require two or more OEs to the same site being carried out at different times while taking the treatment effects into consideration. Such staged OE offers minimum intervention and maximum efficiency. In this case report, OE was first applied for orthodontic extraction. After bone regeneration followed by an implant placement and another surgical operation, a second OE was applied to align the inclination of an adjacent tooth. As a result, a predictable prognosis of implants as well as greatly improved esthetics and periodontal tissue health were achieved.

Early differential processing of material images: Evidence from ERP classification.

Science.gov (United States)

Wiebel, Christiane B; Valsecchi, Matteo; Gegenfurtner, Karl R

2014-06-24

Investigating the temporal dynamics of natural image processing using event-related potentials (ERPs) has a long tradition in object recognition research. In a classical Go-NoGo task two characteristic effects have been emphasized: an early task independent category effect and a later task-dependent target effect. Here, we set out to use this well-established Go-NoGo paradigm to study the time course of material categorization. Material perception has gained more and more interest over the years as its importance in natural viewing conditions has been ignored for a long time. In addition to analyzing standard ERPs, we conducted a single trial ERP pattern analysis. To validate this procedure, we also measured ERPs in two object categories (people and animals). Our linear classification procedure was able to largely capture the overall pattern of results from the canonical analysis of the ERPs and even extend it. We replicate the known target effect (differential Go-NoGo potential at frontal sites) for the material images. Furthermore, we observe task-independent differential activity between the two material categories as early as 140 ms after stimulus onset. Using our linear classification approach, we show that material categories can be differentiated consistently based on the ERP pattern in single trials around 100 ms after stimulus onset, independent of the target-related status. This strengthens the idea of early differential visual processing of material categories independent of the task, probably due to differences in low-level image properties and suggests pattern classification of ERP topographies as a strong instrument for investigating electrophysiological brain activity. © 2014 ARVO.

Morphological images analysis and chromosomic aberrations classification based on fuzzy logic

International Nuclear Information System (INIS)

Souza, Leonardo Peres

2011-01-01

This work has implemented a methodology for automation of images analysis of chromosomes of human cells irradiated at IEA-R1 nuclear reactor (located at IPEN, Sao Paulo, Brazil), and therefore subject to morphological aberrations. This methodology intends to be a tool for helping cytogeneticists on identification, characterization and classification of chromosomal metaphasic analysis. The methodology development has included the creation of a software application based on artificial intelligence techniques using Fuzzy Logic combined with image processing techniques. The developed application was named CHRIMAN and is composed of modules that contain the methodological steps which are important requirements in order to achieve an automated analysis. The first step is the standardization of the bi-dimensional digital image acquisition procedure through coupling a simple digital camera to the ocular of the conventional metaphasic analysis microscope. Second step is related to the image treatment achieved through digital filters application; storing and organization of information obtained both from image content itself, and from selected extracted features, for further use on pattern recognition algorithms. The third step consists on characterizing, counting and classification of stored digital images and extracted features information. The accuracy in the recognition of chromosome images is 93.9%. This classification is based on classical standards obtained at Buckton [1973], and enables support to geneticist on chromosomic analysis procedure, decreasing analysis time, and creating conditions to include this method on a broader evaluation system on human cell damage due to ionizing radiation exposure. (author)

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

Science.gov (United States)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

2012-03-01

We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

Changing patient classification system for hospital reimbursement in Romania.

Science.gov (United States)

Radu, Ciprian-Paul; Chiriac, Delia Nona; Vladescu, Cristian

2010-06-01

To evaluate the effects of the change in the diagnosis-related group (DRG) system on patient morbidity and hospital financial performance in the Romanian public health care system. Three variables were assessed before and after the classification switch in July 2007: clinical outcomes, the case mix index, and hospital budgets, using the database of the National School of Public Health and Health Services Management, which contains data regularly received from hospitals reimbursed through the Romanian DRG scheme (291 in 2009). The lack of a Romanian system for the calculation of cost-weights imposed the necessity to use an imported system, which was criticized by some clinicians for not accurately reflecting resource consumption in Romanian hospitals. The new DRG classification system allowed a more accurate clinical classification. However, it also exposed a lack of physicians' knowledge on diagnosing and coding procedures, which led to incorrect coding. Consequently, the reported hospital morbidity changed after the DRG switch, reflecting an increase in the national case-mix index of 25% in 2009 (compared with 2007). Since hospitals received the same reimbursement over the first two years after the classification switch, the new DRG system led them sometimes to change patients' diagnoses in order to receive more funding. Lack of oversight of hospital coding and reporting to the national reimbursement scheme allowed the increase in the case-mix index. The complexity of the new classification system requires more resources (human and financial), better monitoring and evaluation, and improved legislation in order to achieve better hospital resource allocation and more efficient patient care.

Differing Procedures for Recording Mortality Statistics in Scandinavia

DEFF Research Database (Denmark)

Tøllefsen, Ingvild M.; Hem, Erlend; Ekeberg, Øivind

2017-01-01

Background: There may be various reasons for differences in suicide rates between countries and over time within a country. One reason can be different registration practices. Aims: The purpose of this study was to describe and compare the present procedures for mortality and suicide registration...... in the three Scandinavian countries and to illustrate potential sources of error in the registration of suicide. Method: Information about registration practices and classification procedures was obtained from the cause of death registers in Norway, Sweden, and Denmark. In addition, we received information...... and in postmortem examinations exist in Scandinavian countries. These differences might influence the suicide statistics in Scandinavia....

State-of-the-Art Methods for Brain Tissue Segmentation: A Review.

Science.gov (United States)

Dora, Lingraj; Agrawal, Sanjay; Panda, Rutuparna; Abraham, Ajith

2017-01-01

Brain tissue segmentation is one of the most sought after research areas in medical image processing. It provides detailed quantitative brain analysis for accurate disease diagnosis, detection, and classification of abnormalities. It plays an essential role in discriminating healthy tissues from lesion tissues. Therefore, accurate disease diagnosis and treatment planning depend merely on the performance of the segmentation method used. In this review, we have studied the recent advances in brain tissue segmentation methods and their state-of-the-art in neuroscience research. The review also highlights the major challenges faced during tissue segmentation of the brain. An effective comparison is made among state-of-the-art brain tissue segmentation methods. Moreover, a study of some of the validation measures to evaluate different segmentation methods is also discussed. The brain tissue segmentation, content in terms of methodologies, and experiments presented in this review are encouraging enough to attract researchers working in this field.

Classification of interstitial lung disease patterns with topological texture features

Science.gov (United States)

Huber, Markus B.; Nagarajan, Mahesh; Leinsinger, Gerda; Ray, Lawrence A.; Wismüller, Axel

2010-03-01

Topological texture features were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honey-combing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. A set of 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and three Minkowski Functionals (MFs, e.g. MF.euler). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions and the significance thresholds were adjusted for multiple comparisons by the Bonferroni correction. The best classification results were obtained by the MF features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers. The highest accuracy was found for MF.euler (97.5%, 96.6%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced topological texture features can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

Classification of hydrocephalus: critical analysis of classification categories and advantages of "Multi-categorical Hydrocephalus Classification" (Mc HC).

Science.gov (United States)

Oi, Shizuo

2011-10-01

Hydrocephalus is a complex pathophysiology with disturbed cerebrospinal fluid (CSF) circulation. There are numerous numbers of classification trials published focusing on various criteria, such as associated anomalies/underlying lesions, CSF circulation/intracranial pressure patterns, clinical features, and other categories. However, no definitive classification exists comprehensively to cover the variety of these aspects. The new classification of hydrocephalus, "Multi-categorical Hydrocephalus Classification" (Mc HC), was invented and developed to cover the entire aspects of hydrocephalus with all considerable classification items and categories. Ten categories include "Mc HC" category I: onset (age, phase), II: cause, III: underlying lesion, IV: symptomatology, V: pathophysiology 1-CSF circulation, VI: pathophysiology 2-ICP dynamics, VII: chronology, VII: post-shunt, VIII: post-endoscopic third ventriculostomy, and X: others. From a 100-year search of publication related to the classification of hydrocephalus, 14 representative publications were reviewed and divided into the 10 categories. The Baumkuchen classification graph made from the round o'clock classification demonstrated the historical tendency of deviation to the categories in pathophysiology, either CSF or ICP dynamics. In the preliminary clinical application, it was concluded that "Mc HC" is extremely effective in expressing the individual state with various categories in the past and present condition or among the compatible cases of hydrocephalus along with the possible chronological change in the future.

Classification

Science.gov (United States)

Clary, Renee; Wandersee, James

2013-01-01

In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

Tissue engineering in the treatment of cartilage lesions

Directory of Open Access Journals (Sweden)

Jakob Naranđa

2013-11-01

Full Text Available Background: Articular cartilage lesions with the inherent limited healing potential are difficult to treat and thus remain a challenging problem for orthopaedic surgeons. Regenerative treatment techniques, such as autologous chondrocyte implantation (ACI, are promising as a treatment option to restore hyaline-like cartilage tissue in damaged articular surfaces, as opposed to the traditional reparative procedures (e.g. bone marrow stimulation – microfracture, which promote a fibrocartilage formation with lower tissue biomechanical properties and poorer clinical results. ACI technique has undergone several advances and is constantly improving. The new concept of cartilage tissue preservation uses tissue-engineering technologies, combining new biomaterials as a scaffold, application of growth factors, use of stem cells, and mechanical stimulation. The recent development of new generations of ACI uses a cartilage-like tissue in a 3-dimensional culture system that is based on the use of biodegradable material which serves as a temporary scaffold for the in vitro growth and subsequent implantation into the cartilage defect. For clinical practice, single stage procedures appear attractive to reduce cost and patient morbidity. Finally, modern concept of tissue engineering facilitates hyaline-like cartilage formation and a permanent treatment of cartilage lesions.Conclusion: The review focuses on innovations in the treatment of cartilage lesions and covers modern concepts of tissue engineering with the use of biomaterials, growth factors, stem cells and bioreactors, and presents options for clinical use.

Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement

Directory of Open Access Journals (Sweden)

Ali Soleymani

2014-06-01

Full Text Available Since various behavioral movement patterns are likely to be valid within different, unique ranges of spatial and temporal scales (e.g., instantaneous, diurnal, or seasonal with the corresponding spatial extents, a cross-scale approach is needed for accurate classification of behaviors expressed in movement. Here, we introduce a methodology for the characterization and classification of behavioral movement data that relies on computing and analyzing movement features jointly in both the spatial and temporal domains. The proposed methodology consists of three stages. In the first stage, focusing on the spatial domain, the underlying movement space is partitioned into several zonings that correspond to different spatial scales, and features related to movement are computed for each partitioning level. In the second stage, concentrating on the temporal domain, several movement parameters are computed from trajectories across a series of temporal windows of increasing sizes, yielding another set of input features for the classification. For both the spatial and the temporal domains, the ``reliable scale'' is determined by an automated procedure. This is the scale at which the best classification accuracy is achieved, using only spatial or temporal input features, respectively. The third stage takes the measures from the spatial and temporal domains of movement, computed at the corresponding reliable scales, as input features for behavioral classification. With a feature selection procedure, the most relevant features contributing to known behavioral states are extracted and used to learn a classification model. The potential of the proposed approach is demonstrated on a dataset of adult zebrafish (Danio rerio swimming movements in testing tanks, following exposure to different drug treatments. Our results show that behavioral classification accuracy greatly increases when firstly cross-scale analysis is used to determine the best analysis scale, and

Automatic tissue characterization from ultrasound imagery

Science.gov (United States)

Kadah, Yasser M.; Farag, Aly A.; Youssef, Abou-Bakr M.; Badawi, Ahmed M.

1993-08-01

In this work, feature extraction algorithms are proposed to extract the tissue characterization parameters from liver images. Then the resulting parameter set is further processed to obtain the minimum number of parameters representing the most discriminating pattern space for classification. This preprocessing step was applied to over 120 pathology-investigated cases to obtain the learning data for designing the classifier. The extracted features are divided into independent training and test sets and are used to construct both statistical and neural classifiers. The optimal criteria for these classifiers are set to have minimum error, ease of implementation and learning, and the flexibility for future modifications. Various algorithms for implementing various classification techniques are presented and tested on the data. The best performance was obtained using a single layer tensor model functional link network. Also, the voting k-nearest neighbor classifier provided comparably good diagnostic rates.

SECONDARY PULMONARY ARTERIAL HYPERTENSION IN SYSTEMIC DISEASES OF CONNECTIVE TISSUE

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N. A. Shostak

2016-01-01

Full Text Available Modern definition of pulmonary arterial hypertension (PAH as well as data on prevalence and incidence of secondary PAH in systemic disease of connective tissue is presented,  including data of USA, France and Scotland registers. The main chains of pathogenesis, classification approaches, clinical features and diagnostics are described. 

SECONDARY PULMONARY ARTERIAL HYPERTENSION IN SYSTEMIC DISEASES OF CONNECTIVE TISSUE

Directory of Open Access Journals (Sweden)

N. A. Shostak

2009-01-01

Full Text Available Modern definition of pulmonary arterial hypertension (PAH as well as data on prevalence and incidence of secondary PAH in systemic disease of connective tissue is presented,  including data of USA, France and Scotland registers. The main chains of pathogenesis, classification approaches, clinical features and diagnostics are described. 

Radiation sterilization of tissue allografts: Requirements for validation and routine control. A code of practice

International Nuclear Information System (INIS)

2007-12-01

These recommendations for the radiation sterilization of tissue allografts adopt the principles that the International Organization for Standardization (ISO) applies to the radiation sterilization of health care products. The approach has been adapted to take into account the special features associated with human tissues and the features that distinguish them from industrially produced sterile health care products. The approach as described here is not applicable if viral contamination is identified. Thus it is emphasized that the human donors of the tissues must be medically and serologically screened. To further support this screening it is recommended that autopsy reports be reviewed if available. This adaptation of established ISO methods can thus only be applied to sterilization of tissue allografts if the radiation sterilization described here is the terminal stage of a careful, detailed, documented sequence of procedures involving: donor selection; tissue retrieval; tissue banking general procedures; specific processing procedures; labelling; and distribution. The methods proposed here for the establishment of a sterilization dose are based on statistical approaches used for the sterilization of health care products and modified appropriately for the low numbers of tissue allograft samples typically available. This code of practice will be useful to tissue banking staff, surgeons using tissues for transplantation, regulators who oversee the safety of transplantation and radiation sterilization procedures, members of tissue banking associations, health service personnel in hospitals in which tissue transplantations are performed and inter-governmental organizations involved in transplantation issues, for example the World Health Organization. This publication was discussed extensively at an international meeting in Wrexham in the United Kingdom and was approved by the Technical Advisory Committee of the relevant IAEA project, which included the Chairpersons

Effectiveness of soft tissue diode laser in treatment of oral mucosal lesions

Directory of Open Access Journals (Sweden)

Amanpreet Kaur

2017-01-01

Full Text Available Soft tissue diode lasers are becoming popular among clinicians due to their potential value in surgical procedures providing surface sterilization, dry surgical field, and increased patient acceptance. Two patients with different soft tissue lesions were selected, and soft tissue diode laser was used for excision and wound healing was assessed by visual method with photographs. No discomfort to the patient during and after the laser procedure was observed. Inspite of using minimal local anesthesia, avoiding placement of sutures, and not prescribing any antibiotics, minimal bleeding, no edema, and good wound healing was observed. We conclude that lasers treatments can be superior to conventional approaches with regards to easy ablation, decontamination, and hemostasis, and are less painful during and after the procedure.

Endovascular thrombectomy and post-procedural headache.

Science.gov (United States)

Khan, Sabrina; Amin, Faisal Mohammad; Holtmannspötter, Markus; Hansen, Klaus; Florescu, Anna Maria; Fakhril-Din, Zainab; Petersen, Julie Falkenberg; Ghanizada, Hashmat; Ayata, Cenk; Gaist, David; Ashina, Messoud

2017-12-01

We investigated the prevalence of post-procedural headache in patients who have undergone thrombectomy for ischemic stroke, and correlated history of migraine with risk of peri-procedural complications. A total of 314 patients underwent thrombectomy at the Danish National Hospital from January 2012 to December 2014. Eligible subjects were phone-interviewed using a purpose-developed semi-structured questionnaire according to the International Classification of Headache Disorders 3, beta version criteria. Among 96 eligible subjects, there was a significant decrease in migraine (p = 0.022) within the first 3 months after EVT compared to 1 year before treatment, which was further evident at interview time (on average 1.6 years after EVT, p = 0.013). A minority of patients experienced headaches for the first time within 3 months of their EVT (migraine 2, TTH 9), which persisted at interview time for subjects with migraine. Out of 12 subjects with peri-procedural complications, 2 had a history of migraine with aura. Thrombectomy leads to a significant decrease in previously known migraine, and new onset of headache in a small subset of patients. A history of migraine does not appear to predispose to peri-procedural complications.

Value measurement of nuclear medicine procedures

International Nuclear Information System (INIS)

Potchen, E.J.; Harris, G.I.; Schonbein, W.R.; Rashford, N.J.

1977-01-01

The difficulty in measuring the benefit component for cost/benefit analysis of diagnostic procedures in medicine is portrayed as a complex issue relating the objective of intent to a classification of types of decisions a physician must make in evaluating a patient's problem. Ultimately, it seems desirable to develop measuring instruments such as attitude measurement tools by which the relative value of alternative diagnostic procedures could be measured in terms of what they contribute to diminishing the patient's personal perception of disease. Even without this idealized objective, it is reasonable to assume that diagnostic tests which do not contain information, defined as a change in the randomness of a state of knowledge, could not be expected to ultimately benefit the patient. Thus diagnostic information should provide a rational direction for the physician to modify the course of the patient's illness. Since information can be measured as a change in randomness of a knowledge state, we can determine the information content of a specific nuclear medicine procedure when faced with an array of diagnostic problems. These measurements remain to be made for clinical nuclear medicine procedures and are currently under study

A comparative study of PCA, SIMCA and Cole model for classification of bioimpedance spectroscopy measurements.

Science.gov (United States)

Nejadgholi, Isar; Bolic, Miodrag

2015-08-01

Due to safety and low cost of bioimpedance spectroscopy (BIS), classification of BIS can be potentially a preferred way of detecting changes in living tissues. However, for longitudinal datasets linear classifiers fail to classify conventional Cole parameters extracted from BIS measurements because of their high variability. In some applications, linear classification based on Principal Component Analysis (PCA) has shown more accurate results. Yet, these methods have not been established for BIS classification, since PCA features have neither been investigated in combination with other classifiers nor have been compared to conventional Cole features in benchmark classification tasks. In this work, PCA and Cole features are compared in three synthesized benchmark classification tasks which are expected to be detected by BIS. These three tasks are classification of before and after geometry change, relative composition change and blood perfusion in a cylindrical organ. Our results show that in all tasks the features extracted by PCA are more discriminant than Cole parameters. Moreover, a pilot study was done on a longitudinal arm BIS dataset including eight subjects and three arm positions. The goal of the study was to compare different methods in arm position classification which includes all three synthesized changes mentioned above. Our comparative study on various classification methods shows that the best classification accuracy is obtained when PCA features are classified by a K-Nearest Neighbors (KNN) classifier. The results of this work suggest that PCA+KNN is a promising method to be considered for classification of BIS datasets that deal with subject and time variability. Copyright © 2015 Elsevier Ltd. All rights reserved.

Discrimination of soft tissues using laser-induced breakdown spectroscopy in combination with k nearest neighbors (kNN) and support vector machine (SVM) classifiers

Science.gov (United States)

Li, Xiaohui; Yang, Sibo; Fan, Rongwei; Yu, Xin; Chen, Deying

2018-06-01

In this paper, discrimination of soft tissues using laser-induced breakdown spectroscopy (LIBS) in combination with multivariate statistical methods is presented. Fresh pork fat, skin, ham, loin and tenderloin muscle tissues are manually cut into slices and ablated using a 1064 nm pulsed Nd:YAG laser. Discrimination analyses between fat, skin and muscle tissues, and further between highly similar ham, loin and tenderloin muscle tissues, are performed based on the LIBS spectra in combination with multivariate statistical methods, including principal component analysis (PCA), k nearest neighbors (kNN) classification, and support vector machine (SVM) classification. Performances of the discrimination models, including accuracy, sensitivity and specificity, are evaluated using 10-fold cross validation. The classification models are optimized to achieve best discrimination performances. The fat, skin and muscle tissues can be definitely discriminated using both kNN and SVM classifiers, with accuracy of over 99.83%, sensitivity of over 0.995 and specificity of over 0.998. The highly similar ham, loin and tenderloin muscle tissues can also be discriminated with acceptable performances. The best performances are achieved with SVM classifier using Gaussian kernel function, with accuracy of 76.84%, sensitivity of over 0.742 and specificity of over 0.869. The results show that the LIBS technique assisted with multivariate statistical methods could be a powerful tool for online discrimination of soft tissues, even for tissues of high similarity, such as muscles from different parts of the animal body. This technique could be used for discrimination of tissues suffering minor clinical changes, thus may advance the diagnosis of early lesions and abnormalities.

Perceptual-motor skill learning in Gilles de la Tourette syndrome. Evidence for multiple procedural learning and memory systems.

Science.gov (United States)

Marsh, Rachel; Alexander, Gerianne M; Packard, Mark G; Zhu, Hongtu; Peterson, Bradley S

2005-01-01

Procedural learning and memory systems likely comprise several skills that are differentially affected by various illnesses of the central nervous system, suggesting their relative functional independence and reliance on differing neural circuits. Gilles de la Tourette syndrome (GTS) is a movement disorder that involves disturbances in the structure and function of the striatum and related circuitry. Recent studies suggest that patients with GTS are impaired in performance of a probabilistic classification task that putatively involves the acquisition of stimulus-response (S-R)-based habits. Assessing the learning of perceptual-motor skills and probabilistic classification in the same samples of GTS and healthy control subjects may help to determine whether these various forms of procedural (habit) learning rely on the same or differing neuroanatomical substrates and whether those substrates are differentially affected in persons with GTS. Therefore, we assessed perceptual-motor skill learning using the pursuit-rotor and mirror tracing tasks in 50 patients with GTS and 55 control subjects who had previously been compared at learning a task of probabilistic classifications. The GTS subjects did not differ from the control subjects in performance of either the pursuit rotor or mirror-tracing tasks, although they were significantly impaired in the acquisition of a probabilistic classification task. In addition, learning on the perceptual-motor tasks was not correlated with habit learning on the classification task in either the GTS or healthy control subjects. These findings suggest that the differing forms of procedural learning are dissociable both functionally and neuroanatomically. The specific deficits in the probabilistic classification form of habit learning in persons with GTS are likely to be a consequence of disturbances in specific corticostriatal circuits, but not the same circuits that subserve the perceptual-motor form of habit learning.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

Science.gov (United States)

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries.

Science.gov (United States)

Noor, Siti Salwa Md; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-11-16

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability.

A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

Directory of Open Access Journals (Sweden)

Zekić-Sušac Marijana

2014-09-01

Full Text Available Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods.

Assessing the Accuracy and Consistency of Language Proficiency Classification under Competing Measurement Models

Science.gov (United States)

Zhang, Bo

2010-01-01

This article investigates how measurement models and statistical procedures can be applied to estimate the accuracy of proficiency classification in language testing. The paper starts with a concise introduction of four measurement models: the classical test theory (CTT) model, the dichotomous item response theory (IRT) model, the testlet response…

CLASSIFICATION ALGORITHMS FOR BIG DATA ANALYSIS, A MAP REDUCE APPROACH

Directory of Open Access Journals (Sweden)

V. A. Ayma

2015-03-01

Full Text Available Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP, which is an open-source, distributed framework for automatic image interpretation, is presented. The tool, named ICP: Data Mining Package, is able to perform supervised classification procedures on huge amounts of data, usually referred as big data, on a distributed infrastructure using Hadoop MapReduce. The tool has four classification algorithms implemented, taken from WEKA’s machine learning library, namely: Decision Trees, Naïve Bayes, Random Forest and Support Vector Machines (SVM. The results of an experimental analysis using a SVM classifier on data sets of different sizes for different cluster configurations demonstrates the potential of the tool, as well as aspects that affect its performance.

Dopaminergic Immunofluorescence Studies in Kidney Tissue.

Science.gov (United States)

Gildea, J J; Van Sciver, R E; McGrath, H E; Kemp, B A; Jose, P A; Carey, R M; Felder, R A

2017-01-01

The kidney is a highly integrated system of specialized differentiated cells that are responsible for fluid and electrolyte balance in the body. While much of today's research focuses on isolated nephron segments or cells from nephron segments grown in tissue culture, an often overlooked technique that can provide a unique view of many cell types in the kidney is slice culture. Here, we describe techniques that use freshly excised kidney tissue from rats to perform a variety of experiments shortly after isolating the tissue. By slicing the rat kidney in a "bread loaf" format, multiple studies can be performed on slices from the same tissue in parallel. Cryosectioning and staining of the tissue allow for the evaluation of physiological or biochemical responses in a wide variety of specific nephron segments. The procedures described within this chapter can also be extended to human or mouse kidney tissue.

False-positive reduction in CAD mass detection using a competitive classification strategy

International Nuclear Information System (INIS)

Li Lihua; Zheng Yang; Zhang Lei; Clark, Robert A.

2001-01-01

High false-positive (FP) rate remains to be one of the major problems to be solved in CAD study because too many false-positively cued signals will potentially degrade the performance of detecting true-positive regions and increase the call-back rate in CAD environment. In this paper, we proposed a novel classification method for FP reduction, where the conventional 'hard' decision classifier is cascaded with a 'soft' decision classification with the objective to reduce false-positives in the cases with multiple FPs retained after the 'hard' decision classification. The 'soft' classification takes a competitive classification strategy in which only the 'best' ones are selected from the pre-classified suspicious regions as the true mass in each case. A neural network structure is designed to implement the proposed competitive classification. Comparative studies of FP reduction on a database of 79 images by a 'hard' decision classification and a combined 'hard'-'soft' classification method demonstrated the efficiency of the proposed classification strategy. For example, for the high FP sub-database which has only 31.7% of total images but accounts for 63.5% of whole FPs generated in single 'hard' classification, the FPs can be reduced for 56% (from 8.36 to 3.72 per image) by using the proposed method at the cost of 1% TP loss (from 69% to 68%) in whole database, while it can only be reduced for 27% (from 8.36 to 6.08 per image) by simply increasing the threshold of 'hard' classifier with a cost of TP loss as high as 14% (from 69% to 55%). On the average in whole database, the FP reduction by hybrid 'hard'-'soft' classification is 1.58 per image as compared to 1.11 by 'hard' classification at the TP costs described above. Because the cases with high dense tissue are of higher risk of cancer incidence and false-negative detection in mammogram screening, and usually generate more FPs in CAD detection, the method proposed in this paper will be very helpful in improving

Radiosterilization of Tissues Preserved for Clinical Purposes: Effect on Tissue Antigenicity

International Nuclear Information System (INIS)

Ostrowski, K.; Kossowska, B.; Moskalewski, S.; Komender, A.; Kurnatowski, W.

1967-01-01

The first part of the paper contains practical considerations on the radiosterilization of preserved human bone, human and calf cartilage, cow’s fascia and aponeurosis, based on material from the Tissue Bank which produces about 2500 transplants yearly. The method of preservation and packing of each type of tissue is mentioned briefly. The preserved tissues are irradiated in a cobalt bomb or in a nuclear reactor. The conditions of irradiation and the control of sterility are described. The advantages and disadvantages of radiosterilization are discussed on the basis of the authors’ own experience and clinical reports of surgeons using radiosterilized tissues in practice. In the second part of the paper, experimental studies on the influence of freezing, lyophilization and radiosterilization on tissue antigenicity are reported. The regional lymph node reacts to an antigenic stimulus by an increased production of large, pyroninophylic cells, so-called ''blast'' cells. The rabbits used as recipients received grafts of allogeneic cancellous bone, fresh or subjected to different experimental procedures. Smears from lymph node cell suspension were prepared and the percentage of blast cells was estimated. On the basis of the lymph node response, it appears that freezing and lyophilization, as well as radiosterilization, may abolish the antigenicity of cancellous bone. The practical implication of these results for methods of preservation of tissues for clinical purposes is discussed. (author)

Classification of heterogeneous electron microscopic projections into homogeneous subsets

International Nuclear Information System (INIS)

Herman, G.T.; Kalinowski, M.

2008-01-01

The co-existence of different states of a macromolecular complex in samples used by three-dimensional electron microscopy (3D-EM) constitutes a serious challenge. The single particle method applied directly to such heterogeneous sets is unable to provide useful information about the encountered conformational diversity and produces reconstructions with severely reduced resolution. One approach to solving this problem is to partition heterogeneous projection set into homogeneous components and apply existing reconstruction techniques to each of them. Due to the nature of the projection images and the high noise level present in them, this classification task is difficult. A method is presented to achieve the desired classification by using a novel image similarity measure and solving the corresponding optimization problem. Unlike the majority of competing approaches, the presented method employs unsupervised classification (it does not require any prior knowledge about the objects being classified) and does not involve a 3D reconstruction procedure. We demonstrate a fast implementation of this method, capable of classifying projection sets that originate from 3D-EM. The method's performance is evaluated on synthetically generated data sets produced by projecting 3D objects that resemble biological structures

Hand eczema classification

DEFF Research Database (Denmark)

Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

2008-01-01

of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

Classification of the web

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

International recommendation for a comprehensive neuropathologic workup of epilepsy surgery brain tissue: A consensus Task Force report from the ILAE Commission on Diagnostic Methods.

Science.gov (United States)

Blümcke, Ingmar; Aronica, Eleonora; Miyata, Hajime; Sarnat, Harvey B; Thom, Maria; Roessler, Karl; Rydenhag, Bertil; Jehi, Lara; Krsek, Pavel; Wiebe, Samuel; Spreafico, Roberto

2016-03-01

Epilepsy surgery is an effective treatment in many patients with drug-resistant focal epilepsies. An early decision for surgical therapy is facilitated by a magnetic resonance imaging (MRI)-visible brain lesion congruent with the electrophysiologically abnormal brain region. Recent advances in the pathologic diagnosis and classification of epileptogenic brain lesions are helpful for clinical correlation, outcome stratification, and patient management. However, application of international consensus classification systems to common epileptic pathologies (e.g., focal cortical dysplasia [FCD] and hippocampal sclerosis [HS]) necessitates standardized protocols for neuropathologic workup of epilepsy surgery specimens. To this end, the Task Force of Neuropathology from the International League Against Epilepsy (ILAE) Commission on Diagnostic Methods developed a consensus standard operational procedure for tissue inspection, distribution, and processing. The aims are to provide a systematic framework for histopathologic workup, meeting minimal standards and maximizing current and future opportunities for morphofunctional correlations and molecular studies for both clinical care and research. Whenever feasible, anatomically intact surgical specimens are desirable to enable systematic analysis in selective hippocampectomies, temporal lobe resections, and lesional or nonlesional neocortical samples. Correct orientation of sample and the sample's relation to neurophysiologically aberrant sites requires good communication between pathology and neurosurgical teams. Systematic tissue sampling of 5-mm slabs along a defined anatomic axis and application of a limited immunohistochemical panel will ensure a reliable differential diagnosis of main pathologies encountered in epilepsy surgery. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Gender differences of athletes in different classification groups of sports and sport disciplines

Directory of Open Access Journals (Sweden)

Olena Tarasevych

2016-04-01

Full Text Available Purpose: to identify the percentage of masculine, androgynous and feminine figures in different classification groups, sports and sports disciplines, depending on the sport qualification. Material & Methods: the study was conducted on the basis of the Kharkiv State Academy of Physical Culture among students – representatives of different sports that have different athletic skills using analysis and compilation of scientific and methodical literature, survey, testing the procedure S. Bam "Masculinity / femininity "Processing and statistical data. Results: based on the testing method established S. Bam percentage masculine, androgynous and feminine personalities among athletes and athletes in various sports classification groups depending on their athletic skills. Conclusions: among sportsmen and women in a variety of classification groups of sports is not revealed feminine personalities; masculine identity, among both men and women predominate in sports; androgyny attitude towards men and women are different.

Security classification of information

Energy Technology Data Exchange (ETDEWEB)

Quist, A.S.

1993-04-01

This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

Analysis of Influence of Different Relations Types on the Quality of Thesaurus Application to Text Classification Problems

Directory of Open Access Journals (Sweden)

Nadezhda S. Lagutina

2017-01-01

Full Text Available The main purpose of the article is to analyze how effectively different types of thesaurus relations can be used for solutions of text classification tasks. The basis of the study is an automatically generated thesaurus of a subject area, that contains three types of relations: synonymous, hierarchical and associative. To generate the thesaurus the authors use a hybrid method based on several linguistic and statistical algorithms for extraction of semantic relations. The method allows to create a thesaurus with a sufficiently large number of terms and relations among them. The authors consider two problems: topical text classification and sentiment classification of large newspaper articles. To solve them, the authors developed two approaches that complement standard algorithms with a procedure that take into account thesaurus relations to determine semantic features of texts. The approach to topical classification includes the standard unsupervised BM25 algorithm and the procedure, that take into account synonymous and hierarchical relations of the thesaurus of the subject area. The approach to sentiment classification consists of two steps. At the first step, a thesaurus is created, whose terms weight polarities are calculated depending on the term occurrences in the training set or on the weights of related thesaurus terms. At the second step, the thesaurus is used to compute the features of words from texts and to classify texts by the algorithm SVM or Naive Bayes. In experiments with text corpora BBCSport, Reuters, PubMed and the corpus of articles about American immigrants, the authors varied the types of thesaurus relations that are involved in the classification and the degree of their use. The results of the experiments make it possible to evaluate the efficiency of the application of thesaurus relations for classification of raw texts and to determine under what conditions certain relationships affect more or less. In particular, the

Soft tissue engineering with micronized-gingival connective tissues.

Science.gov (United States)

Noda, Sawako; Sumita, Yoshinori; Ohba, Seigo; Yamamoto, Hideyuki; Asahina, Izumi

2018-01-01

The free gingival graft (FGG) and connective tissue graft (CTG) are currently considered to be the gold standards for keratinized gingival tissue reconstruction and augmentation. However, these procedures have some disadvantages in harvesting large grafts, such as donor-site morbidity as well as insufficient gingival width and thickness at the recipient site post-treatment. To solve these problems, we focused on an alternative strategy using micronized tissue transplantation (micro-graft). In this study, we first investigated whether transplantation of micronized gingival connective tissues (MGCTs) promotes skin wound healing. MGCTs (≤100 µm) were obtained by mincing a small piece (8 mm 3 ) of porcine keratinized gingiva using the RIGENERA system. The MGCTs were then transplanted to a full skin defect (5 mm in diameter) on the dorsal surface of immunodeficient mice after seeding to an atelocollagen matrix. Transplantations of atelocollagen matrixes with and without micronized dermis were employed as experimental controls. The results indicated that MGCTs markedly promote the vascularization and epithelialization of the defect area 14 days after transplantation compared to the experimental controls. After 21 days, complete wound closure with low contraction was obtained only in the MGCT grafts. Tracking analysis of transplanted MGCTs revealed that some mesenchymal cells derived from MGCTs can survive during healing and may function to assist in wound healing. We propose here that micro-grafting with MGCTs represents an alternative strategy for keratinized tissue reconstruction that is characterized by low morbidity and ready availability. © 2017 Wiley Periodicals, Inc.

Classification of clinical autofluorescence spectra of oral leukoplakia using an artificial neural network : a pilot study

NARCIS (Netherlands)

van Staveren, HJ; van Veen, RLP; Speelman, OC; Witjes, MJH; Roodenburg, JLN

The performance of an artificial neural network was evaluated as an alternative classification technique of autofluorescence spectra of oral leukoplakia, which may reflect the grade of tissue dysplasia. Twenty-two visible lesions of 21 patients suffering from oral leukoplakia and six locations on

Radiation processing of biological tissues for nuclear disaster management

International Nuclear Information System (INIS)

Singh, Rita

2012-01-01

A number of surgical procedures require tissue substitutes to repair or replace damaged or diseased tissues. Biological tissues from human donor like bone, skin, amniotic membrane and other soft tissues can be used for repair or reconstruction of the injured part of the body. Tissues from human donor can be processed and banked for orthopaedic, spinal, trauma and other surgical procedures. Allograft tissues provide an excellent alternative to autografts. The use of allograft tissue avoids the donor site morbidity and reduces the operating time, expense and trauma associated with the acquisition of autografts. Further, allografts have the added advantage of being available in large quantities. This has led to a global increase in allogeneic transplantation and development of tissue banking. However, the risk of infectious disease transmission via tissue allografts is a major concern. Therefore, tissue allografts should be sterilized to make them safe for clinical use. Radiation processing has well appreciated technological advantages and is the most suitable method for sterilization of biological tissues. Radiation processed biological tissues can be provided by the tissue banks for the management of injuries due to a nuclear disaster. A nuclear detonation will result in a large number of casualties due to the heat, blast and radiation effects of the weapon. Skin dressings or skin substitutes like allograft skin, xenograft skin and amniotic membrane can be used for the treatment of thermal burns and radiation induced skin injuries. Bone grafts can be employed for repairing fracture defects, filling in destroyed regions of bone, management of open fractures and joint injuries. Radiation processed tissues have the potential to repair or reconstruct damaged tissues and can be of great assistance in the treatment of injuries due to the nuclear weapon. (author)

[Lasers in dentistry. Part B--Interaction with biological tissues and the effect on the soft tissues of the oral cavity, the hard tissues of the tooth and the dental pulp].

Science.gov (United States)

Moshonov, J; Stabholz, A; Leopold, Y; Rosenberg, I; Stabholz, A

2001-10-01

The interaction of laser energy with target tissue is mainly determined by two non operator-dependent factors: the specific wavelength of the laser and the optical properties of the target tissues. Power density, energy density, pulse repetition rate, pulse duration and the mode of energy transferring to the tissue are dictated by the clinician. Combination of these factors enables to control optimal response for the clinical application. Four responses are described when the laser beam hits the target tissue: reflection, absorption, transmission and scattering. Three main mechanisms of interaction between the laser and the biological tissues exist: photothermic, photoacoustic and photochemical. The effect of lasers on the soft tissues of the oral cavity is based on transformation of light energy into thermal energy which, in turn heats the target tissue to produce the desirable effect. In comparison to the scalpel used in surgical procedures, the laser beam is characterized by tissue natural sterility and by minimum bleeding during the surgical procedures due to blood vessels welding. The various effects achieved by the temperature elevation during the laser application on the soft tissue are: I. coagulation and hemostasis II. tissue sterilization III. tissue welding IV. incision and excision V. ablation and vaporization Ablation and melting are the two basic modalities by which the effect of lasers on the hard tissues of the tooth is produced. When discussing the effect of laser on dental hard tissues, the energy absorption in the hydroxyapatite plays a major role in addition to its absorption in water. When laser energy is absorbed in the water of the hard tissues, a rapid volume expansion of the evaporating water occurs as a result of a substantial temperature elevation in the interaction site. Microexplosions are produced causing hard tissue disintegration. If pulp temperatures are raised beyond 5 degrees C level, damage to the dental pulp is irreversible

Malignant fatty tumors: classification, clinical course, imaging appearance and treatment

International Nuclear Information System (INIS)

Peterson, J.J.; Kransdorf, M.J.; Bancroft, L.W.; O'Connor, M.I.

2003-01-01

Liposarcoma is a relatively common soft tissue malignancy with a wide spectrum of clinical presentations and imaging appearances. Several subtypes are described, ranging from lesions nearly entirely composed of mature adipose tissue, to tumors with very sparse adipose elements. The imaging appearance of these fatty masses is frequently sufficiently characteristic to allow a specific diagnosis, while in other cases, although a specific diagnosis is not achievable, a meaningful limited differential diagnosis can be established. The purpose of this paper is to review the spectrum of malignant fatty tumors, highlighting the current classification system, clinical presentation and behavior, treatment and spectrum of imaging appearances. The imaging review will emphasize CT scanning and MR imaging, and will stress differentiating radiologic features. (orig.)

Tissue adhesives for simple traumatic lacerations.

Science.gov (United States)

Beam, Joel W

2008-01-01

using a standard form. The primary measure was cosmetic outcome. Secondary measures were pain with the procedure, time to complete the procedure, and complications (erythema, infection, discharge, need for delayed closure, and dehiscence). Studies were divided into 2 groups as follows: group 1, comparisons among tissue adhesives with SWC, and group 2, comparisons among different tissue adhesives. All eligible studies were assessed for methodologic quality independently by 2 investigators using the Jadad Scale, which evaluates randomization, double blinding, withdrawals, and dropouts and is scored on a 5-point (maximum) scale. The data from the tissue adhesive and SWC studies were pooled and analyzed with a random-effects model. The I (2) statistic was used to determine heterogeneity among the studies. chi (2) analysis was performed to compare participant age, wound location, and type of tissue adhesive among the studies. The data from the studies comparing tissue adhesives were pooled and analyzed using a fixed-effects model. The search criteria identified 39 eligible studies, of which 11 met the inclusion criteria. In 10 studies, a tissue adhesive was compared with SWC. Five groups used butylcyanoacrylate, and 5 used octylcyanoacrylate. For SWC, 6 groups used sutures, 2 used adhesive strips, and 2 used a combination of methods, although most used sutures. Six studies were limited to pediatric patients and 2 to adult patients; 2 included patients of any age. Wounds were limited to facial lacerations in 2 pediatric studies and 1 group with patients of any age. Lacerations requiring deep sutures were excluded in 4 studies. One group compared tissue adhesives (butylcyanoacrylate and octylcyanoacrylate) among pediatric patients with facial lacerations not requiring deep sutures. In the 11 included studies, authors of 9 randomized and evaluated 1 laceration per patient, whereas 2 groups included patients with more than 1 laceration. In 1 group, each laceration was

Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.

Science.gov (United States)

Wu, Shang-Lin; Liao, Lun-De; Lu, Shao-Wei; Jiang, Wei-Ling; Chen, Shi-An; Lin, Chin-Teng

2013-08-01

Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.

Dialog act classification with the help of prosody

OpenAIRE

Mast, Marion; Kompe, Ralf; Harbeck, Stefan; Kießling, Andreas; Niemann, Heinrich; Nöth, Elmar

1996-01-01

This paper presents automatic methods for the segmentation and classication of dialog acts (DA). In Verbmobil it is often sufficient to recognize the sequence of DAs occurring during a dialog between the two partners. Since a turn can consist of one or more successive DAs we conduct the classification of DAs in a two step procedure: First each turn has to be segmented into units which correspond to a DA and second the DA categories have to be identified. For the segmentation we use polygrams ...

Hazard classification methodology

International Nuclear Information System (INIS)

Brereton, S.J.

1996-01-01

This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

The value of virtual touch tissue image (VTI) and virtual touch tissue quantification (VTQ) in the differential diagnosis of thyroid nodules

International Nuclear Information System (INIS)

Zhang, Feng-Juan; Han, Ruo-Ling; Zhao, Xin-Ming

2014-01-01

Highlights: • All nodules in the research were confirmed by histopathology. • The classification method of VTI was easy to learn. • VTQ could provide quantitative elasticity measurements for thyroid nodules. • VTI classification could provide semi-quantitative elasticity analysis. • The area ratio could show invasive extent of malignant tumor. - Abstract: Objectives: To explore the value of virtual touch tissue image (VTI) and virtual touch tissue quantification (VTQ) in the differential diagnosis of thyroid nodules. Methods: One-hundred and seven patients with 113 thyroid nodules were performed conventional ultrasound and acoustic radiation force impulse (ARFI) elastography. The stiffness of the nodules on virtual touch tissue image (VTI) was graded, and the area ratios (AR) of nodules on VTI images versus on B-mode images were calculated. Shear wave velocity (SWV) within the thyroid nodules were measured using virtual touch tissue quantification (VTQ) technique. The pathological diagnosis as the gold standard draws the receiver-operating characteristic curve (ROC) to find the cut-off point of VTI grades, AR and SWV to predict thyroid cancer. Results: The difference in VTI grades of malignant and benign nodules was statistically significant (P < 0.05), as well as in AR and SWV. There was no significant difference in the AR of nodules or the SWV of nodules in benign group or in malignant group. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of VTI grades, AR, and SWV in the differential diagnosis of thyroid nodules were calculated. There was no significant difference in diagnostic accuracy among the three methods. Conclusion: VTI grades, AR of nodules on VTI images versus on B-mode images and SWV within the nodules can help the differential diagnosis of thyroid nodules

AIRPORTS CLASSIFICATION AND PRIORITY OF THEIR RECONSTRUCTION