bluuebunny/crossref_metadata_2025 huggingface dataset:
Early outcome in endoscopic extended endonasal approach for removal of supradiaphragmatic craniopharyngiomas: a case series and a comprehensive review
Authors: Bosnjak Roman , Benedicic Mitja , Vittori Alenka
Published: June 2013

Background. The choice of endoscopic expanded endonasal approach introduces the possibility of improved gross total resection of craniopharyngioma while minimizing surgical morbidity in a significant subset of patients.

Methods. From our trans-sphenoidal surgical series of 331 cases, we retrospectively reviewed visual, endocrine and neuro-cognitive outcomes in the first consecutive eight patients (median age 63 years; range 47-73 years) with newly diagnosed supradiaphragmatic craniopharyngioma (median tumour height 23 mm; range 15-34 mm), removed by expanded endonasal approach (median follow-up 27 months; range 10-69 months). Gross total resection was attempted in all patients.

Results. Gross total resection was achieved in 6 of 8 patients. Visual improvement was present in 6 of 8 patients of patients or in 14 of 16 eyes. New endocrinopathy, including diabetes insipidus, appeared in 5 of 8 patients. Stalk was preserved in 4 patients. Cognitive decline was present in 2 cases. Five of 8 patients retained previous quality of life.

Conclusions. Our early outcome results are comparable to the recent few expanded endonasal approach series, except for the incidence of new endocrinopathy and cerebrospinal fluid leak rate. This was influenced by higher number of transinfundibular tumours in our series, where stalk preservation is less likely, and not using nasoseptal flap or gasket closure in the first half of cases. Including data from the literature and ours, expanded endonasal approach shows a trend for improved gross total resection rate with less morbidity, more obviously for visual outcome and quality of life than for endocrine outcome. However, validity of expanded endonasal approach should be confirmed in a larger number of patients with a longer follow-up period.
Role of contrast-enhanced ultrasound in evaluating the efficiency of ultrasound guided percutaneous microwave ablation in patients with renal cell carcinoma
Authors: Li Xin , Liang Ping , Yu Jie , Yu Xiao-Ling , Liu Fang-Yi , Cheng Zhi-Gang , Han Zhi-Yu
Published: June 2013

Background. The aim of the study was to evaluate the efficiency and feasibility of contrast-enhanced ultrasound (CEUS) with Sonovue in assessing of renal cell carcinomas (RCCs) following ultrasound (US)-guided percutaneous microwave ablation (MWA).

Patients and methods. Seventy-nine patients (60 males and 19 females) with 83 lesions (mean size 3.2±1.6 cm) were treated by US-guided percutaneous MWA. The CEUS results of the third day after the ablation were compared with the synchronous contrast-enhanced computed tomography (CT)/magnetic resonance imaging (MRI) results and biopsy pathological results. The follow-up was performed by CEUS and CT/MRI after 1, 3, 6 months and every 6 months subsequently. The combination of clinical follow-up results and CT/MRI imaging findings was the reference standard of CEUS results for evaluating the therapeutic effect. The identification of residual or recurrence tumour was assessed by two blinded radiologists.

Results. On the third day after MWA, CEUS showed 68 of 83 lesions (68/83, 81.9%) successfully ablated and 15 of 83 (18.1%) with residual tumours. Among residual tumours, 13 (86.7%) were confirmed by contrast-enhanced CT/MRI findings and biopsy results. The sensitivity, specificity, accuracy, positive and negative predictive value of CEUS evaluating the short-term MWA effectiveness were 100%, 97.1%, 97.6%, 86.7% and 100%, respectively. During the six years follow-up (median 26 months), the CEUS showed recurrence in 7 patients, and six of them achieved consistent results on CEUS and CT/MRI imaging. The sensitivity, specificity, accuracy, positive and negative predictive value for CEUS evaluating long-term MWA effectiveness were 85.7%, 98.7%, 97.6%, 85.7% and 98.7%, respectively.

Conclusions. The post-procedural CEUS demonstrated as an effective and feasible method in evaluating a therapeutic effect of RCCs following MWA.
Evaluation of a software system for estimating planned dose error in patients, based on planar IMRT QA measurements
Authors: Bakhtiari Mohammad , Parniani Ashkan , Lerma Fritz , Reynolds Shannon , Jordan James , Sedaghat Alireza , Sarfaraz Mehrdad , Rodgers James
Published: June 2013

Background. Intensity modulated radiation therapy (IMRT) dosimetry verification is routinely conducted via integrated or individual field dosimetry using film or a matrix of detectors. Techniques and software systems are commercially available which use individual field dosimetry measurements as input into algorithms that estimate 3D patient dose distributions on CT scan derived target volumes and organs at risk (OARs), thus allowing direct dose-volume histogram (DVH) analysis vs. treatment planning system (TPS) DVH. The purpose of this work is to present a systematic benchmarking technique to evaluate the accuracy and consistency of such a software system.

Methods. A MapCheck2 diode array and 3DVH™ software from Sun Nuclear were used for this study. Delivered planar dose was measured with the diode array as an input to 3DVH™ software that was used to estimate the 3D dose matrix. Accuracy of the output of 3DVH™ is tested by comparing measured planar doses over a range of depths to the same planes reconstructed by 3DVH™. Different fields from complex IMRT cases were selected and examined in this study. The sensitivity to depth of measurement was evaluated.

Results. The Gamma Index analysis, comparing calculated 3D dose with measured 3D dose with 2% and 2mm distance-to-agreement (DTA) criteria returned a pass rate of > 90% for all patient cases calculated by the treatment planning system and it returned a pass rate of > 96% in 9 out of 10 cases calculated by 3DVH™. Extracted computed dose planes with 3DVH™ software at different depths in the flat phantom passed all gamma evaluation analyses when compared to measured planes at different depths using MapCheck2.

Conclusions. Studying complex head and neck IMRT fields, it was shown that the 3D dose distribution predicted by the planned dose perturbation (PDP) algorithm is both accurate and consistent.
Flow structure and cooling behavior of air impingement on a target plate
Authors: Abdul Rasool Adnan , Hamad Faik
Published: June 2013

An experimental data of flow field, pressure coefficient and heat transfer of a jet impinging normally on a flat target plate are presented. The measurements of temperatures and static pressures were carried out for flow from three orifices of 5, 10 and 20 mm diameter for orifice-to-target plate distances of 5, 10, 25, 50, 70, 100 and 120 mm from the orifice exit. The axial development of flow structure of the jet from the orifice was investigated by measuring the radial jet velocity distributions at the same axial distances used to measure heat transfer and static pressure. The results show that pressure coefficients distributions on the target plate are similar to the velocity distributions in the impinging jet which indicates the strong relationship between the two parameters. The pressure coefficients from large orifice diameter are higher than the values from the small orifice diameter for same orifice-to-target plate distance. The results also show a nonlinear increase of heat transfer rate with orifice size and the ratio of axial distance to orifice diameter (X/d). The nonlinear behaviour may be attributed to the complex nature of flow structure at the stagnation region. The high velocity gradients at the stagnation zone leads to higher turbulence and comparatively higher values of heat transfer rates for large orifice diameter.
Antioxidant Properties of Seeds from Lines of Artichoke, Cultivated Cardoon and Wild Cardoon
Authors: Durazzo Alessandra , Foddai Maria , Temperini Andrea , Azzini Elena , Venneria Eugenia , Lucarini Massimo , Finotti Enrico , Maiani Gianluca , Crinò Paola , Saccardo Francesco , Maiani Giuseppe
Published: June 2013

The artichoke (Cynara cardunculus L. subsp. scolymus L.), the cultivated cardoon (Cynara cardunculus var. altilis DC.) and the wild cardoon (Cynara cardunculus var. sylvestris L.) are species widely distributed in the Mediterranean area. The aim of this research was to evaluate the antioxidant properties of seeds from lines of artichoke and cultivated and wild cardoon in both aqueous-organic extracts and their residues by FRAP (Ferric Reducing Antioxidant Power) and TEAC (Trolox Equivalent Antioxidant Capacity) evaluations. Both artichoke and cardoon seeds are a good source of antioxidants. Among artichoke seeds, hydrolysable polyphenols contribution to antioxidant properties ranged from 41% to 78% for FRAP values and from 17% to 37% for TEAC values. No difference between cultivated and wild cardoon in antioxidant properties are reported. Our results could provide information about the potential industrial use and application of artichoke and/or cardoon seeds.
The Heme-Based Oxygen-Sensor Phosphodiesterase Ec DOS (DosP): Structure-Function Relationships
Authors: Shimizu Toru
Published: June 2013

Escherichia coli Direct Oxygen Sensor (Ec DOS, also known as Ec DosP) is a heme-based O2-sensing phosphodiesterase from Escherichia coli that catalyzes the conversion of cyclic-di-GMP to linear di-GMP. Cyclic-di-GMP is an important second messenger in bacteria, highlighting the importance of understanding structure-function relationships of Ec DOS. Ec DOS is composed of an N-terminal heme-bound O2-sensing PAS domain and a C-terminal phosphodiesterase catalytic domain. Notably, its activity is markedly enhanced by O2 binding to the heme Fe(II) complex in the PAS sensor domain. X-ray crystal structures and spectroscopic and catalytic characterization of the wild-type and mutant proteins have provided important structural and functional clues to understanding the molecular mechanism of intramolecular catalytic regulation by O2 binding. This review summarizes the intriguing findings that have obtained for Ec DOS.
Welcome to Inorganics: A New Open Access, Inclusive Forum for Inorganic Chemistry
Authors: Gregory Duncan
Published: June 2013

One of the beauties of inorganic chemistry is its sheer diversity. Just as chemistry sits at the centre of the sciences, inorganic chemistry sits at the centre of chemistry itself. Inorganic chemists are fortunate in having the entire periodic table at their disposal, providing a palette for the creation of a multitude of rich and diverse compounds and materials from the simplest salts to the most complex of molecular species. It follows that the language of inorganic chemistry can thus be a demanding one, accommodating sub-disciplines with very different perspectives and frames of reference. One could argue that it is the unequivocal breadth of inorganic chemistry that empowers inorganic chemists to work at the interfaces, not just between the traditional Inorganic-Organic-Physical boundaries of the discipline, but in the regions where chemistry borders the other physical and life sciences, engineering and socio-economics. [...]
Impedimetric DNA Biosensor Based on a Nanoporous Alumina Membrane for the Detection of the Specific Oligonucleotide Sequence of Dengue Virus
Authors: Deng Jiajia , Toh Chee-Seng
Published: June 2013

A novel and integrated membrane sensing platform for DNA detection is developed based on an anodic aluminum oxide (AAO) membrane. Platinum electrodes (~50–100 nm thick) are coated directly on both sides of the alumina membrane to eliminate the solution resistance outside the nanopores. The electrochemical impedance technique is employed to monitor the impedance changes within the nanopores upon DNA binding. Pore resistance (Rp) linearly increases in response towards the increasing concentration of the target DNA in the range of 1 × 10−12 to 1 × 10−6 M. Moreover, the biosensor selectively differentiates the complementary sequence from single base mismatched (MM-1) strands and non-complementary strands. This study reveals a simple, selective and sensitive method to fabricate a label-free DNA biosensor.
Optimal geometry for a quartz multipurpose SPM sensor
Authors: Stirling Julian
Published: June 2013

We propose a geometry for a piezoelectric SPM sensor that can be used for combined AFM/LFM/STM. The sensor utilises symmetry to provide a lateral mode without the need to excite torsional modes. The symmetry allows normal and lateral motion to be completely isolated, even when introducing large tips to tune the dynamic properties to optimal values.
SUSTAINABILITY ASSESSMENT OF HEAVY METALS AND ROAD MAINTENANCE SALTS IN SWEEP SAND FROM ROADSIDE ENVIRONMENT
Authors: Kazlauskienė Agnė , Valentukevičienė Marina , Ignatavičius Gytautas
Published: June 2013

The main aim of this study was to characterize heavy metal compounds of sweep sand particles in the city of Vilnius (Lithuania). These research results provide new insight into the distribution and variation of heavy metal compounds in sweep sand in the studied area. The results of this investigation reflect the level of heavy metal pollution during the winter season, thus can be used to judge the quality of storm water flowing from streets. The major heavy metals found to have accumulated were lead, nickel, zinc and copper. These research results are useful for conducting preliminary evaluations of possible heavy metal pollution in other similar cities within the European Union. The general anthropogenic factor of three main types of land-use has the greatest influence on contamination of urban topsoil. In industrial sites, concentrations of key contaminants (Pb, Cu, Mn, Ni) are significantly higher than in residential and public–residential areas. The present article discussed the significance of systematic sustainable evaluation as one of the most important activities associated with a sustainable approach. Consequently, to reduce a negative effect of salts on street environment, measures of environmentally sustainable development have to be undertaken.
ASSET-BASED APPROACH TO POVERTY REDUCTION IN LITHUANIA
Authors: Laurinavičius Algimantas , Galinienė Birutė
Published: June 2013

This paper reviews the articles of Lithuanian authors on social policy topic and assesses if the asset-based policy topic was ever explored. It briefly analyses the efficiency of current social security policy in Lithuania and social-economical state of inhabitants. It states that in order to reduce poverty and inequality, current social policy should be reformed, and the current income support (or income security) policy should be replaced by the asset-based policy which stresses the development of skills, knowledge and capabilities, promotes savings, investments and building of assets and gives everyone a possibility to become a capital owner. The paper presents results of a representative survey which was aimed to explore Lithuanian inhabitants’ opinion towards the new form of social policy: asset-based policy. It uncovers that vast majority of Lithuania's inhabitants would agree to the implementation of the asset-based policy, based on children's savings accounts.
Essai de modélisation de la constitution des équipes entrepreneuriales
Authors: Ben-Hafaïedh Cyrine
Published: June 2013

Les équipes entrepreneuriales sont à l’origine de près d’une création d’entreprise sur deux en France. Elles sont la clé de voûte de ces entreprises généralement plus performantes que les autres. Mais ces équipes peinent souvent à se constituer et les projets collectifs échouent fréquemment à cause des équipes qui implosent. La littérature offre deux approches théoriques, a priori opposées, de la constitution des équipes entrepreneuriales : une approche stratégique et une approche socio-psychologique. Sur la base d’une étude qualitative abductive de dix équipes entrepreneuriales, nous examinons la participation de ces deux principales approches théoriques à la compréhension du phénomène de constitution des équipes entrepreneuriales. Nous proposons, in fine, un modèle renouvelé du phénomène, plus proche de la réalité étudiée et combinant ces deux approches contrastées. Les implications managériales, en termes d’accompagnement notamment, sont soulignées.
Communautés d'affaires et réseaux sociaux : facteur de développement stratégique pour l'internationalisation des entreprises ?
Authors: Goxe François
Published: June 2013

Ceci est un résumé de notre thèse qui conceptualise l’internationalisation comme un processus entrepreneurial de passage d’un champ social à un autre par un individu, grâce notamment à ses « réseaux ». Cette conceptualisation, appliquée aux cas d’entrepreneurs de PME françaises en Chine, révèle que : 1) Les caractéristiques personnelles ne prennent pleinement d’utilité qu’en fonction de l’accueil qui leur est fait par les acteurs établis. 2) Cet accueil dépend de l’incorporation d’un certain « esprit » (habitus) par les nouveaux venus. Le cosmopolitisme et le rejet des appartenances nationales fondent des divisions entre acteurs internationaux et expliquent en partie le succès ou l’échec des entrepreneurs. 3) L’accompagnement à l’international nécessite une sensibilisation précoce au fonctionnement des communautés étrangères et à leurs « cultures », mais surtout à la culture des communautés d’affaires internationales.
Les performances des réseaux d'accompagnement entrepreneurial
Authors: Pluchart Jean-Jacques
Published: June 2013

Les études sur les processus d’accompagnement des créateurs d’entreprises et sur la mesure de leurs performances sont encore émergentes. L’étude restituée dans cet article s’efforce d’identifier les différents types de réseaux d’accompagnement des créateurs d’entreprise, puis d’en comparer les indicateurs de mesure des performances. L’étude repose sur l’analyse comparée des trajectoires suivies par 37 projets de créations de PME accompagnées par une pépinière d’entreprises d’Ile-de-France. Elle fait principalement appel à la méthode originale des études de cas narratives quantifiées.
Real and Virtual Spaces of Revisiting the Question “What to Do With Folklore?”
Authors: Klobčar Marija
Published: June 2013

In 1975, the question “What to do with folklore?” very clearly expressed the position of Slovenian folklore studies of the time. It was aimed at society, which the experts deemed indifferent towards tradition. A new examination primarily asks whether today this question can be addressed to the same audience and ask the same thing. Is it once more directed at society, or does it perhaps demand self-reflection by scholars, who, without extensive theoretical consideration, often find it difficult to justify their research topic and presence today?
***
Leta 1975 je vprašanje Kam bi s to folkloro? zelo jasno izrazilo stališča tedanje slovenske folkloristike. Namenjeno je bilo družbi, po presoji stroke brezbrižni do izročila. Vnovično soočenje z njim pa je predvsem dilema, ali ima lahko danes to vprašanje istega naslovnika in enako vsebino. Ali je spet namenjeno družbi ali pa morda zahteva samorefeksijo stroke, ki brez širokega teoretskega premisleka marsikdaj težko opraviči predmet svojega raziskovanja in svojo navzočnost v sodobnosti?
Folklore and Ethno-Nationalism in Mexican American Literary Production. Adaptation and Transformation of Indigenous Folk Icons in the Chicano Movement
Authors: Herrera-Sobek Maria
Published: June 2013

In this study I examine the adaptation and transformation of indigenous myths and legends, particularly the La Llorona, La Malinche and the Virgin of Guadalupe myths, within the explosive Mexican American ethno-nationalist movement from the turbulent 1960s and thereafter. I posit that ethno-nationalist movements as well as nationalist movements arising from marginalized groups in a nation find folk traditions indispensable for political resistance and affirmation purposes as well as for literary production which I argue is an integral part of nationalist movements.
***
V tej razpravi obravnavam prilagajanje in spreminjanje domačinskih mitov in legend, zlasti mitov o Lloroni (Jokajoči ženi), Malinche (ženi Marini) in Devici guadelupski, v vznesenem mehiško-ameriškem etnonacionalističnem gibanju od razburkanih 60. let prejšnjega stoletja naprej. Ugotavljam, da etnonacionalistična kakor tudi nacionalistična gibanja zapostavljenih skupin v naciji najdejo v ljudskem izročilu močno oporo za politični odpor in samouveljavitev, pa tudi za literarno produkcijo, ki jo razumem kot sestavino nacionalističnih gibanj.
International Cooperation. Anna Bērzkalne
Authors: Treija Rita
Published: June 2013

Cooperation among professional folklore researchers is a considerable issue for the history of the discipline. In the 1920s and 1930s, the most noteworthy Latvian partner in the then existing international collaboration network was Anna Bērzkalne (1891–1956). She was a representative of the historic-geographical method in Latvian folkloristics. Anna Bērzkalne was very enthusiastic about providing Latvian folklore materials to researchers abroad. She in return also received support to her studies and research.
***
Sodelovanje med poklicnimi raziskovalci folklore je pomembno vprašanje v zgodovini discipline. V 20. in 30. letih 20. stoletja je bila v Latviji v mednarodnih stikih najopaznejša Anna Bērzkalne (1891–1956). Bila je predstavnica zgodovinsko-geografske metode v latvijski folkloristiki. Anna Bērzkalne je latvijsko folklorno izročilo z navdušenjem posredovala tujim raziskovalcem, prav tako pa je bila tudi sama deležna podpore pri svojem raziskovanju.
Image Analysis
Authors: Droege Detlev
Published: June 2013

This chapter focuses on the image processing part of eye tracking systems. Basic knowledge of image processing is assumed. After an overview of the possible input images and some remarks on preprocessing of the images, we will focus on the detection relevant features such as pupils and glints. The last part of this chapter focuses on estimating positions of these features. It is not possible to present a comprehensive solution for an eye tracker in this chapter; however, we will indicate possible yet simplified methods in the different steps of processing and demonstrate how images can be processed to obtain real-time performance. The program code is given in Matlab (Octave) language for clarity.
A Study of Cloud Computing for Retinal Image Processing through MATLAB
Authors: Maharana S. K. , Prabhakar P. Ganesh , Bhati Amit
Published: June 2013

With the ability of MATLAB to run in the cloud environment the authors analyse a retinal image efficiently. A quick and on-the-fly image processing is the cause for leveraging the ability of Cloud with the classic computing power of MATLAB. This cloud-based image processing has significantly saved on the cost of procuring resources and it has processed an image in a few seconds. This revolutionary change in computing power has not only eased the life of engineering community but has demonstrated an inertia to help the common man through its language of computing. The objective of this particular piece of work is to leverage the ubiquitous cloud features to process the images taken from retina portion through a hi-fidelity algorithm. The reflection of the computing ability of complex mathematical equations, SaaS (Soft as a Service) architecture of cloud and tools developed in Windows Azure platform has come out as research findings such as the spatial modelling of a diseased portion of a retina. The portion diagnosed with a difficulty undergoes a series of steps based on the algorithm developed by authors and ultimately the original image is transformed into a form with information on the status of the disease in the retina.
Projective Geometry for 3D Modeling of Objects
Authors: Elias Rimon
Published: June 2013

This chapter surveys many fundamental aspects of projective geometry that have been used extensively in computer vision literature. In particular, it discusses the role of this branch of geometry in reconstructing basic entities (e.g., 3D points, 3D lines, and planes) in 3D space from multiple images. The chapter presents the notation of different elements. It investigates the geometrical relationships when one or two cameras are observing the scene creating single-view and two-view geometry. In other words, camera parameters in terms of locations and orientations, with respect to 3D space and with respect to other cameras, create relationships. This chapter discusses these relationships and expresses them mathematically. Finally, different approaches to deal with the existence of noise or inaccuracy in general are presented.
Image Focus Measure Based on Energy of High Frequency Components in S-Transform
Authors: Mahmood Muhammad Tariq , Choi Tae-Sun
Published: June 2013

Focus measure computes sharpness or high frequency contents in an image. It plays an important role in many image processing and computer vision applications such as shape from focus (SFF) techniques and multi-focus image fusion algorithms. In this chapter, we discuss different focus measures in spatial as well as in the transform domains. In addition, we suggest a novel focus measure in S-transform domain, which is based on the energy of high frequency components. A localized spectrum, by using variable window size, provides a more accurate method of measuring image sharpness as compared to other focus measures proposed in spectral domains. An optimal focus measure is obtained by selecting an appropriate frequency dependent window width. The performance of the proposed focus measure is compared with those of existing focus measures in terms of three dimensional shape recovery and all-in-focus image generation. Experimental results demonstrate the effectiveness of the proposed focus measure.
Object Recognition with a Limited Database Using Shape Space Theory
Authors: Han Yuexing , Wang Bing , Koike Hideki , Idesawa Masanori
Published: June 2013

One of the main goals of image understanding and computer vision applications is to recognize an object from various images. Object recognition has been deeply developed for the last three decades, and a lot of approaches have been proposed. Generally, these methods of object recognition can successfully achieve their goal by relying on a large quantity of data. However, if the observed objects are shown to diverse configurations, it is difficult to recognize them with a limited database. One has to prepare enough data to exactly recognize one object with multi-configurations, and it is hard work to collect enough data only for a single object. In this chapter, the authors will introduce an approach to recognize objects with multi-configurations using the shape space theory. Firstly, two sets of landmarks are obtained from two objects in two-dimensional images. Secondly, the landmarks represented as two points are projected into a pre-shape space. Then, a series of new intermediate data can be obtained from data models in the pre-shape space. Finally, object recognition can be achieved in the shape space with the shape space theory.
Fast and High Capacity Digital Image Watermarking Technique Based on Phase of Zernike Moments
Authors: Walia Ekta , Suneja Anu
Published: June 2013

Zernike Moments (ZMs) are used in many image processing applications, due to their resistance against various signal processing and geometric attacks. Digital image watermarking is one of those application areas, where ZMs are widely used to insert and extract the watermark bits for digital media authentication. In all the existing ZM based watermarking techniques, magnitude of moments is used to insert and extract the watermark. In this paper, the authors’ have proposed a semi blind watermarking technique in which phase of ZMs is used for watermark insertion and extraction. Due to the use of phase of ZMs, 100% detection ratio is achieved against any geometric and other signal processing attacks. To make the proposed technique fast, q-recursive method is used to compute the Zernike polynomials. The use of q-recursive method has also increased the transparency of watermark due to its better reconstruction ability as compared to traditional moment computation method. Through detailed experimentation, it has been confirmed that the proposed watermarking technique is fast, has more imperceptibility, less Bit Error Rate (BER) and more capacity as compared to traditional ZMs magnitude based watermarking technique.
An Evaluation Framework and a Benchmark for Multi/Hyperspectral Image Compression
Authors: Delcourt Jonathan , Mansouri Alamin , Sliwa Tadeusz , Voisin Yvon
Published: June 2013

This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach (Full 3D and Hybrid). All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed. Results of this comparison show the weaknesses and strengths of each approach.
A Hierarchical Multilevel Image Thresholding Method Based on the Maximum Fuzzy Entropy Principle
Authors: Guan Pearl P. , Yan Hong
Published: June 2013

Image thresholding and edge detection are crucial in image processing and understanding. In this chapter, the authors propose a hierarchical multilevel image thresholding method for edge information extraction based on the maximum fuzzy entropy principle. In order to realize multilevel thresholding, a tree structure is used to express the histogram of an image. In each level of the tree structure, the image is segmented by three-level thresholding based on the maximum fuzzy entropy principle. In theory, the histogram hierarchy can be combined arbitrarily with multilevel thresholding. The proposed method is proven by experimentation to retain more edge information than existing methods employing several grayscale images. Furthermore, the authors extend the multilevel thresholding algorithm for color images in the application of content-based image retrieval, combining with edge direction histograms. Compared to using the original images, experimental results show that the thresholding images outperform in achieving higher average precision and recall.
A Novel Fuzzy Rule Guided Intelligent Technique for Gray Image Extraction and Segmentation
Authors: Mondal Koushik
Published: June 2013

Image segmentation and subsequent extraction from a noise-affected background, has all along remained a challenging task in the field of image processing. There are various methods reported in the literature to this effect. These methods include various Artificial Neural Network (ANN) models (primarily supervised in nature), Genetic Algorithm (GA) based techniques, intensity histogram based methods, et cetera. Providing an extraction solution working in unsupervised mode happens to be even more interesting a problem. Fuzzy systems concern fundamental methodology to represent and process uncertainty and imprecision in the linguistic information. The fuzzy systems that use fuzzy rules to represent the domain knowledge of the problem are known as Fuzzy Rule Base Systems (FRBS). Literature suggests that effort in this respect appears to be quite rudimentary. This chapter proposes a fuzzy rule guided novel technique that is functional devoid of any external intervention during execution. Experimental results suggest that this approach is an efficient one in comparison to different other techniques extensively addressed in literature. In order to justify the supremacy of performance of our proposed technique in respect of its competitors, the author takes recourse to effective metrices like Mean Squared Error (MSE), Mean Absolute Error (MAE), and Peak Signal to Noise Ratio (PSNR).
Hypergraph Based Visual Segmentation and Retrieval
Authors: Huang Yuchi
Published: June 2013

This chapter explores original techniques for the construction of hypergraph models for computer vision applications. A hypergraph is a generalization of a pairwise simple graph, where an edge can connect any number of vertices. The expressive power of the hypergraph models places a special emphasis on the relationship among three or more objects, which has made hypergraphs better models of choice in a lot of problems. This is in sharp contrast with the more conventional graph representation of visual patterns where only pairwise connectivity between objects is described. This chapter draws up from three aspects to carry the discussion of hypergraph based methods in computer vision: (i) The advantage of the hypergraph neighborhood structure is analyzed. The author argues that the summarized local grouping information contained in hypergraphs causes an ‘averaging’ effect which is beneficial to the clustering problems; (ii)The chapter discusses how to build hypergraph incidence structures and how to solve the related unsupervised and semi-supervised problems for two different computer vision scenarios: video object segmentation and image retrieval; (iii) For the application of image retrieval, the chapter introduces a novel hypergraph model — probabilistic hypergraph to exploit the structure of the data manifold by considering not only the local grouping information, but also the similarities between vertices in hyperedges.
Graph Embedding Using Dissimilarities with Applications in Classification
Authors: Bunke Horst , Riesen Kaspar
Published: June 2013

The domain of graphs contains only little mathematical structure. That is, most of the basic mathematical operations, actually required by many standard computer vision and pattern recognition algorithms, are not available for graphs. One of the few mathematical concepts that has been successfully transferred from the vector space to the graph domain is distance computation between graphs, commonly referred to as graph matching. Yet, distance-based pattern recognition is basically limited to nearest-neighbor classification. The present chapter reviews a novel approach for graph embedding in vector spaces built upon the concept of graph matching. The key-idea of the proposed embedding method is to use the distances of an input graph to a number of training graphs, termed prototypes, as vectorial description of the graph. That is, all graph matching procedures proposed in the literature during the last decades can be employed in this embedding framework. The rationale for such a graph embedding is to bridge the gap between the high representational power and flexibility of graphs and the large amount of algorithms available for object representations in terms of feature vectors. Hence, the proposed framework can be considered a contribution towards unifying the domains of structural and statistical pattern recognition.
Artificial Visual Attention Using Combinatorial Pyramids
Authors: Antúnez E. , Haxhimusa Y. , Marfil R. , Kropatsch W. G. , Bandera A.
Published: June 2013

Computer vision systems have to deal with thousands, sometimes millions of pixel values from each frame, and the computational complexity of many problems related to the interpretation of image data is very high. The task becomes especially difficult if a system has to operate in real-time. Within the Combinatorial Pyramid framework, the proposed computational model of attention integrates bottom-up and top-down factors for attention. Neurophysiologic studies have shown that, in humans, these two factors are the main responsible ones to drive attention. Bottom-up factors emanate from the scene and focus attention on regions whose features are sufficiently discriminative with respect to the features of their surroundings. On the other hand, top-down factors are derived from cognitive issues, such as knowledge about the current task. Specifically, the authors only consider in this model the knowledge of a given target to drive attention to specific regions of the image. With respect to previous approaches, their model takes into consideration not only geometrical properties and appearance information, but also internal topological layout. Once the focus of attention has been fixed to a region of the scene, the model evaluates if the focus is correctly located over the desired target. This recognition algorithm considers topological features provided by the pre-attentive stage. Thus, attention and recognition are tied together, sharing the same image descriptors.
ICA as Pattern Recognition Technique for Gesture Identification
Authors: Naik Ganesh , Kumar Dinesh Kant , Arjunan Sridhar
Published: June 2013

In recent times there is an urgent need for a simple yet robust system to identify natural hand actions and gestures for controlling prostheses and other computer assisted devices. Surface Electromyogram (sEMG) is a non-invasive measure of the muscle activities but is not reliable because there are multiple simultaneously active muscles. This research first establishes the conditions for the applicability of Independent Component Analysis (ICA) pattern recognition techniques for sEMG. Shortcomings related to order and magnitude ambiguity have been identified and a mitigation strategy has been developed by using a set of unmixing matrix and neural network weight matrix corresponding to the specific user. The experimental results demonstrate a marked improvement in the accuracy. The other advantages of this system are that it is suitable for real time operations and it is easy to train by a lay user.
IVUS Image Processing Methodologies
Authors: Sakellarios Antonis A. , Bourantas Christos V. , Athanasiou Lambros S. , Fotiadis Dimitrios I. , Michalis Lampros K.
Published: June 2013

Intravascular Ultrasound (IVUS) is an invasive imaging technique that allows detailed visualization of the arterial lumen and outer vessel wall and permits characterization of the type of the plaque and quantification of its burden. Traditionally IVUS processing was performed manually. However, it became apparent that manual segmentation is time consuming, and the obtained results depend on the experience of the operators. To overcome these limitations and enhance the role of IVUS in clinical practice and research, several (semi-) automated methods have been developed that expedite detection of the regions of interest and/or characterization of the type of the plaque. In this chapter we review the available IVUS processing techniques and present the developed commercial solutions for IVUS segmentation and plaque characterization.
Surgeon Assistive Augmented Reality Model with the use of Endoscopic Camera for Line of Vision Calculation
Authors: Daskalaki Anastasia , Giokas Kostas , Koutsouris Dimitris
Published: June 2013

In this paper, the authors describe a surgeon assistive Augmented Reality (AR) model for endoscopic procedures. They analyze the main parts of the model and the processes that need to be established such as, the registration of the patient, the segmentation of medical data, their 3D reconstruction, and the detection of endoscopic instruments and the camera. The authors present two graphical user interfaces, build to serve the needs of segmentation, navigation, and visualization of the final intra-operative scene. By using preoperative data of the patient (MRI-CT) and image processing techniques, the authors can provide a unique view of the surgical scene. The potentials and the advantages of endoscopic-robotic surgeries nowadays can be improved. Augmented surgery scenes with information about the patients underline structures, enables wider situation awareness, precision, and confidence.
Computational Intelligence Techniques for Pattern Recognition in Biomedical Image Processing Applications
Authors: Hemanth D. Jude , Anitha J.
Published: June 2013

Medical image classification is one of the most widely used methodologies in the biomedical field for abnormality detection in the anatomy of the human body. Image classification belongs to the broad category of pattern recognition in which different abnormal images are grouped into different categories based on the nature of the pathologies. Nowadays, these techniques are automated and high accuracy combined with low convergence rate has become the desired features of automated techniques. Artificial Intelligence (AI) techniques are the highly preferred automated techniques because of superior performance measures. In this chapter, the application of AI techniques for pattern recognition is explored in the context of abnormal Magnetic Resonance (MR) brain image classification. This chapter illustrates the theory behind the AI techniques and their effectiveness for practical application in medical image classification. Few experimental results are also provided to aid the conclusions. Algorithmic approach of the AI techniques such as neural networks, fuzzy theory, and genetic algorithm are also dealt in this chapter.
Adaptive Intelligent Systems for Recognition of Cancerous Cervical Cells Based on 2D Cervical Cytological Digital Images
Authors: Ane Bernadetta Kwintiana , Roller Dieter
Published: June 2013

To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women in the world. Papanicolau smear test is a well-known screening method of detecting abnormalities of the cervix cells. Due to scarce number of skilled and experienced cytologists, the screening procedure becomes time consuming and highly prone to human errors that leads to inaccurate and inconsistent diagnosis. This condition increases the risk of patients who get HPV infection not be detected and become HPV carriers. Coping with this problem, an adaptive intelligent system is developed to enable automatic recognition of cancerous cells from. Here pattern recognition is done based on three morphological cell characteristics, i.e. size, shape, and color features, and measured as numerical values in terms of N/C ratio, nucleus perimeter, nucleus radius, cell deformity, texture heterogeneity, wavelet approximation coefficients, and gray-level intensity. Through a supervised learning of multilayer perceptron network, the system is able to percept abnormality in the cervix cells, and to assign them into a predicted group membership, i.e. normal or cancerous cells. Based on thorough observation upon the selected features and attributes, it can be recognized that the cancerous cells follow certain patterns and highly distinguishable from the normal cells.
Virtual Forensic Anthropology
Authors: Davy-Jow Stephanie L. , Decker Summer J. , Schofield Damian
Published: June 2013

Anthropology is the “study of man” and encompasses a diverse range of topics, including socio-cultural studies, linguistics, archaeology, and physical anthropology. Physical anthropology, or “biological” anthropology, the study of humans both living and deceased, can be further subcategorized into osteology, primatology, human evolution, and forensic anthropology. Forensic anthropology is the application of physical anthropology techniques to medico-legal settings. Virtual Reality (VR) is being applied to forensic anthropology in a multitude of ways to benefit research and teaching. Several large-scale projects have been launched to digitize, reconstruct, and disseminate specimens (for example, http://www.virtual-anthropology.com). This chapter will begin with an overview of the discipline of forensic anthropology and discuss a number of representative applications of VR technology in this field that are changing the way in which case work may be handled in the future.
Computational Intelligence for Pathological Issues in Precision Agriculture
Authors: Sannakki Sanjeev S. , Rajpurohit Vijay S. , Nargund V. B. , Kumar Arun R. , Yallur Prema S.
Published: June 2013

Plant Pathology is the scientific study of plant diseases, caused by pathogens and environmental conditions (physiological factors). Detection and grading of plant diseases by machine vision is an essential research topic as it may prove useful in monitoring large fields of crops. This can be of great benefit to those users, who have little or no information about the crop they are growing. Also, in some developing countries, farmers may have to go long distances to contact experts to dig up information which is expensive and time consuming. Therefore, looking for a fast, automatic, less expensive, and accurate method to detect plant diseases is of great realistic significance. Such an efficient system can be modeled by integrating the various tools/techniques of information and communication technology (ICT) in agriculture. The objective of the present chapter is to model an intelligent decision support system for detection and grading of plant diseases which encompasses image processing techniques and soft computing/machine learning techniques.
In-Line Sorting of Processed Fruit Using Computer Vision
Authors: Blasco J. , Aleixos N. , Cubero S. , Albert F. , Lorente D. , Gómez-Sanchis J.
Published: June 2013

Nowadays, there is a growing demand for quality fruits and vegetables that are simple to prepare and consume, like minimally processed fruits. These products have to accomplish some particular characteristics to make them more attractive to the consumers, like a similar appearance and the total absence of external defects. Although recent advances in machine vision have allowed for the automatic inspection of fresh fruit and vegetables, there are no commercially available equipments for sorting of minority processed fruits, like arils of pomegranate (Punica granatum L) or segments of Satsuma mandarin (Citrus unshiu) ready to eat. This work describes a complete solution based on machine vision for the automatic inspection and classification of these fruits based on their estimated quality. The classification is based on morphological and colour features estimated from images taken in-line, and their analysis using statistical methods in order to grade the fruit into commercial categories.
Video Stream Mining for On-Road Traffic Density Analytics
Authors: Hota Rudra Narayan , Jonna Kishore , Krishna P. Radha
Published: June 2013

Traffic congestion problem is rising day-by-day due to increasing number of small to heavy weight vehicles on the road, poorly designed infrastructure, and ineffective control systems. This chapter addresses the problem of estimating computer vision based traffic density using video stream mining. We present an efficient approach for traffic density estimation using texture analysis along with Support Vector Machine (SVM) classifier, and describe analyzing traffic density for on-road traffic congestion control with better flow management. This approach facilitates integrated environment for users to derive traffic status by mining the available video streams from multiple cameras. It also facilitates processing video frames received from video cameras installed in traffic posts and classifies the frames according to traffic content at any particular instance. Time series information available from various input streams is combined with traffic video classification results to discover traffic trends.
Security Applications Using Computer Vision
Authors: Sasi Sreela
Published: June 2013

Computer vision plays a significant role in a wide range of homeland security applications. The homeland security applications include: port security (cargo inspection), facility security (embassy, power plant, bank), and surveillance (military or civilian), et cetera. Video surveillance cameras are placed in offices, hospitals, banks, ports, parking lots, parks, stadiums, malls, train stations, airports, et cetera. The challenge is not for acquiring surveillance data from these video cameras, but for identifying what is valuable, what can be ignored, and what demands immediate attention. Computer vision systems attempt to construct meaningful and explicit descriptions of the environment or scene captured in an image. A few Computer Vision based security applications are presented here for securing building facility, railroad (Objects on railroad, and red signal detection), and roads.