Computer vision techniques in seafood quality control

The application of computer vision based quality control has been slowly but steadily gaining importance mainly due to its speed in achieving results and also greatly due to its non- destnictive nature of testing. Besides, in food applications it also does not contribute to contamination. However, computer vision applications in quality control needs the application of an appropriate software for image analysis. Eventhough computer vision based quality control has several advantages, its application has limitations as to the type of work to be done, particularly so in the food industries. Selective applications, however, can be highly advantageous and very accurate.Computer vision based image analysis could be used in morphometric measurements of fish with the same accuracy as the existing conventional method. The method is non-destructive and non-contaminating thus providing anadvantage in seafood processing.The images could be stored in archives and retrieved at anytime to carry out morphometric studies for biologists.Computer vision and subsequent image analysis could be used in measurements of various food products to assess uniformity of size. One product namely cutlet and product ingredients namely coating materials such as bread crumbs and rava were selected for the study. Computer vision based image analysis was used in the measurements of length, width and area of cutlets. Also the width of coating materials like bread crumbs was measured.Computer imaging and subsequent image analysis can be very effectively used in quality evaluations of product ingredients in food processing. Measurement of width of coating materials could establish uniformity of particles or the lack of it. The application of image analysis in bacteriological work was also done

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

Structured Light System Calibration for Perception in Underwater Tanks

The process of visually exploring underwater environments is still a complex problem. Underwater vision systems require complementary means of sensor information to help overcome water disturbances. This work proposes the development of calibration methods for a structured light based system consisting on a camera and a laser with a line beam. Two different calibration procedures that require only two images from different viewpoints were developed and tested in dry and underwater environments. Results obtained show, an accurate calibration for the camera/projector pair with errors close to 1 mm even in the presence of a small stereos baseline.

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Introduction

Although increasing our knowledge of the properties of networks of cities is essential, these properties can be measured at the city level, and must be assessed by analyzing actor networks. The present volume focuses less on individual characteristics and more on the interactions of actors and institutions that create functional territories in which the structure of existing links constrains emerging links. Rather than basing explanations on external factors, the goal is to determine the extent to which network properties reflect spatial distributions and create local synergies at the meso level that are incorporated into global networks at the macro level where different geographical scales occur. The paper introduces the way to use the graphs structure to identify empirically relevant groups and levels that explain dynamics. It defines what could be called âeurooemulti-levelâeuro, âeurooemulti-scaleâeuro, or âeurooemultidimensionalâeuro networks in the context of urban geography. It explains how the convergence of the network multi-territoriality paradigm collaboratively formulated, and manipulated by geographers and computer scientists produced the SPANGEO project, which is exposed in this volume.

A Small World Perspective on Urban Systems

The theory of small-world networks as initiated by Watts and Strogatz (1998) has drawn new insights in spatial analysis as well as systems theory. The theoryâeuro?s concepts and methods are particularly relevant to geography, where spatial interaction is mainstream and where interactions can be described and studied using large numbers of exchanges or similarity matrices. Networks are organized through direct links or by indirect paths, inducing topological proximities that simultaneously involve spatial, social, cultural or organizational dimensions. Network synergies build over similarities and are fed by complementarities between or inside cities, with the two effects potentially amplifying each other according to the âeurooepreferential attachmentâeuro hypothesis that has been explored in a number of different scientific fields (Barabási, Albert 1999; Barabási A-L 2002; Newman M, Watts D, Barabàsi A-L). In fact, according to Barabási and Albert (1999), the high level of hierarchy observed in âeurooescale-free networksâeuro results from âeurooepreferential attachmentâeuro, which characterizes the development of networks: new connections appear preferentially close to nodes that already have the largest number of connections because in this way, the improvement in the network accessibility of the new connection will likely be greater. However, at the same time, network regions gathering dense and numerous weak links (Granovetter, 1985) or network entities acting as bridges between several components (Burt 2005) offer a higher capacity for urban communities to benefit from opportunities and create future synergies. Several methodologies have been suggested to identify such denser and more coherent regions (also called communities or clusters) in terms of links (Watts, Strogatz 1998; Watts 1999; Barabási, Albert 1999; Barabási 2002; Auber 2003; Newman 2006). These communities not only possess a high level of dependency among their member entities but also show a low level of âeurooevulnerabilityâeuro, allowing for numerous redundancies (Burt 2000; Burt 2005). The SPANGEO project 2005âeuro"2008 (SPAtial Networks in GEOgraphy), gathering a team of geographers and computer scientists, has included empirical studies to survey concepts and measures developed in other related fields, such as physics, sociology and communication science. The relevancy and potential interpretation of weighted or non-weighted measures on edges and nodes were examined and analyzed at different scales (intra-urban, inter-urban or both). New classification and clustering schemes based on the relative local density of subgraphs were developed. The present article describes how these notions and methods contribute on a conceptual level, in terms of measures, delineations, explanatory analyses and visualization of geographical phenomena.

Dose-dependent change in biomarkers during neoadjuvant endocrine therapy with fulvestrant: results from NEWEST, a randomized Phase II study

NEWEST (Neoadjuvant Endocrine Therapy for Women with Estrogen-Sensitive Tumors) is the first study to compare biological and clinical activity of fulvestrant 500 versus 250 mg in the neoadjuvant breast cancer setting. We hypothesized that fulvestrant 500 mg may be superior to 250 mg in blocking estrogen receptor (ER) signaling and growth. A multicenter, randomized, open-label, Phase II study was performed to compare fulvestrant 500 mg (500 mg/month plus 500 mg on day 14 of month 1) versus fulvestrant 250 mg/month for 16 weeks prior to surgery in postmenopausal women with ER+ locally advanced breast cancer. Core biopsies at baseline, week 4, and surgery were assessed for biomarker changes. Primary endpoint: change in Ki67 labeling index (LI) from baseline to week 4 determined by automated computer imaging system (ACIS). Secondary endpoints: ER protein expression and function; progesterone receptor (PgR) expression; tumor response; tolerability. ER and PgR were examined retrospectively using the H score method. A total of 211 patients were randomized (fulvestrant 500 mg: n = 109; 250 mg: n = 102). At week 4, fulvestrant 500 mg resulted in greater reduction of Ki67 LI and ER expression versus 250 mg (-78.8 vs. -47.4% [p < 0.0001] and -25.0 vs. -13.5% [p = 0.0002], respectively [ACIS]); PgR suppression was not significantly different (-22.7 vs. -17.6; p = 0.5677). However, H score detected even greater suppression of ER (-50.3 vs. -13.7%; p < 0.0001) and greater PgR suppression (-80.5 vs. -46.3%; p = 0.0018) for fulvestrant 500 versus 250 mg. At week 16, tumor response rates were 22.9 and 20.6% for fulvestrant 500 and 250 mg, respectively, with considerable decline in all markers by both ACIS and H score. No detrimental effects on endometrial thickness or bone markers and no new safety concerns were identified. This provides the first evidence of greater biological activity for fulvestrant 500 versus 250 mg in depleting ER expression, function, and growth.

Dental Pulp Vascular Permeability Changes Induced by Dental Bleaching

Aiming to compare the effect of different light sources for dental bleaching on vascular permeability of dental pulps, forty-eight incisors were used. The bleaching agent (35% hydrogen peroxide) was activated by halogen light; LED (Light Emitting Diode) or LED, followed by laser phototherapy (LPT) (lambda = 780 nm; 3 J/cm(2)). After the bleaching procedures, the animals received an intra-arterial dye injection and one hour later were sacrificed. The teeth were diaphanized and photographed. The amount of blue stain content of each dental pulp was quantified using a computer imaging program. The data was statistically compared (p <= 0.05). The results showed a significant higher (p <= 0.01) dye content in the groups bleached with halogen light, compared with the control, LED and LED plus LPT groups. Thus, tooth bleaching activated by LED or LED plus LPT induces lesser resulted in increased vascular permeability than halogen light.

Avaliação do vigor de sementes de milho superdoce por meio da análise computadorizada de imagens de plântulas

O presente trabalho foi conduzido com o objetivo de verificar a eficiência do sistema computadorizado de avaliação do vigor de sementes (SVIS®), em comparação com outros procedimentos disponíveis, em sementes de milho superdoce. Foram utilizadas sementes dos híbridos SWB 551 e SWB 585, cada uma representada por cinco lotes, conduzindo-se testes de germinação, envelhecimento acelerado (tradicional e com solução saturada de NaCl) e emergência de plântulas em campo. Para a determinação do vigor das sementes por meio do SVIS®, as plântulas foram avaliadas aos três dias após a semeadura do teste de germinação, sendo obtidos dados referentes ao índice de vigor, à uniformidade de desenvolvimento e ao comprimento de plântulas. Para ambos os híbridos avaliados, os resultados fornecidos pelo SVIS® foram coerentes com os do teste de envelhecimento acelerado tradicional. Concluiu-se que o SVIS® é eficiente para avaliação do vigor de sementes de milho superdoce, constituindo alternativa viável para a determinação do potencial fisiológico.

Dental pulp vascular permeability changes induced by dental bleaching

Aiming to compare the effect of different light sources for dental bleaching on vascular permeability of dental pulps, forty-eight incisors were used. The bleaching agent (35 % hydrogen peroxide) was activated by halogen light; LED (Light Emitting Diode) or LED, followed by laser phototherapy (LPT) (λ = 780 nm; 3 J/cm²). After the bleaching procedures, the animals received an intra-arterial dye injection and one hour later were sacrificed. The teeth were diaphanized and photographed. The amount of blue stain content of each dental pulp was quantified using a computer imaging program. The data was statistically compared (p < 0.05). The results showed a significant higher (p < 0.01) dye content in the groups bleached with halogen light, compared with the control, LED and LED plus LPT groups. Thus, tooth bleaching activated by LED or LED plus LPT induces lesser resulted in increased vascular permeability than halogen light.

Accuracy of computer-aided ultrasound as compared with magnetic resonance imaging in the evaluation of nonalcoholic fatty liver disease in obese and eutrophic adolescents

AbstractObjective:To compare the accuracy of computer-aided ultrasound (US) and magnetic resonance imaging (MRI) by means of hepatorenal gradient analysis in the evaluation of nonalcoholic fatty liver disease (NAFLD) in adolescents.Materials and Methods:This prospective, cross-sectional study evaluated 50 adolescents (aged 11–17 years), including 24 obese and 26 eutrophic individuals. All adolescents underwent computer-aided US, MRI, laboratory tests, and anthropometric evaluation. Sensitivity, specificity, positive and negative predictive values and accuracy were evaluated for both imaging methods, with subsequent generation of the receiver operating characteristic (ROC) curve and calculation of the area under the ROC curve to determine the most appropriate cutoff point for the hepatorenal gradient in order to predict the degree of steatosis, utilizing MRI results as the gold-standard.Results:The obese group included 29.2% girls and 70.8% boys, and the eutrophic group, 69.2% girls and 30.8% boys. The prevalence of NAFLD corresponded to 19.2% for the eutrophic group and 83% for the obese group. The ROC curve generated for the hepatorenal gradient with a cutoff point of 13 presented 100% sensitivity and 100% specificity. As the same cutoff point was considered for the eutrophic group, false-positive results were observed in 9.5% of cases (90.5% specificity) and false-negative results in 0% (100% sensitivity).Conclusion:Computer-aided US with hepatorenal gradient calculation is a simple and noninvasive technique for semiquantitative evaluation of hepatic echogenicity and could be useful in the follow-up of adolescents with NAFLD, population screening for this disease as well as for clinical studies.