Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Automatic Image Annotation Using SURF Descriptors

In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics.

The Effect of SIFT Features as Content Descriptors in the Context of Automatic Writer Identification in Malayalam Language

The span of writer identification extends to broad domes like digital rights administration, forensic expert decisionmaking systems, and document analysis systems and so on. As the success rate of a writer identification scheme is highly dependent on the features extracted from the documents, the phase of feature extraction and therefore selection is highly significant for writer identification schemes. In this paper, the writer identification in Malayalam language is sought for by utilizing feature extraction technique such as Scale Invariant Features Transform (SIFT).The schemes are tested on a test bed of 280 writers and performance evaluated

Selection of Marine Yeasts for the Generation of Single Cell Protein from Prawn-shell Waste

Marine yeasts (33 strains) were isolated from the coastal and offshore waters off Cochin. The isolates were identified and then characterized for the utilization of starch, gelatin, lipid, cellulose, urea, pectin, lignin, chitin and prawn-shell waste. Most of the isolates were Candida species. Based on the biochemical characterization, four potential strains were selected and their optimum pH and NaCI concentration for growth were determined. These strains were then inoculated into prawn-shell waste and SCP (single cell protein) generation was noted in terms of the increase in protein content of the final product.

Matrix based Key Generation to Enhance Key Avalanche in Advanced Encryption Standard

In symmetric block ciphers, substitution and diffusion operations are performed in multiple rounds using sub-keys generated from a key generation procedure called key schedule. The key schedule plays a very important role in deciding the security of block ciphers. In this paper we propose a complex key generation procedure, based on matrix manipulations, which could be introduced in symmetric ciphers. The proposed key generation procedure offers two advantages. First, the procedure is simple to implement and has complexity in determining the sub-keys through crypt analysis. Secondly, the procedure produces a strong avalanche effect making many bits in the output block of a cipher to undergo changes with one bit change in the secret key. As a case study, matrix based key generation procedure has been introduced in Advanced Encryption Standard (AES) by replacing the existing key schedule of AES. The key avalanche and differential key propagation produced in AES have been observed. The paper describes the matrix based key generation procedure and the enhanced key avalanche and differential key propagation produced in AES. It has been shown that, the key avalanche effect and differential key propagation characteristics of AES have improved by replacing the AES key schedule with the Matrix based key generation procedure

Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques

This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

Automatic Optic Disc Boundary Extraction from Color Fundus Images

Efficient optic disc segmentation is an important task in automated retinal screening. For the same reason optic disc detection is fundamental for medical references and is important for the retinal image analysis application. The most difficult problem of optic disc extraction is to locate the region of interest. Moreover it is a time consuming task. This paper tries to overcome this barrier by presenting an automated method for optic disc boundary extraction using Fuzzy C Means combined with thresholding. The discs determined by the new method agree relatively well with those determined by the experts. The present method has been validated on a data set of 110 colour fundus images from DRION database, and has obtained promising results. The performance of the system is evaluated using the difference in horizontal and vertical diameters of the obtained disc boundary and that of the ground truth obtained from two expert ophthalmologists. For the 25 test images selected from the 110 colour fundus images, the Pearson correlation of the ground truth diameters with the detected diameters by the new method are 0.946 and 0.958 and, 0.94 and 0.974 respectively. From the scatter plot, it is shown that the ground truth and detected diameters have a high positive correlation. This computerized analysis of optic disc is very useful for the diagnosis of retinal diseases

Study on Microcredit in Kerala with Special Reference to Employment and Income Generation through Microenterprises and Livelihood Projects

This study aimed to study the evolution and substance of microfinance as a major tool for combating poverty at the global and national level. The development of micro finance in Kerala is briefly discussed. It also indicates the importance and role of microcredit in bringing the poor up in the society through entrepreneurial initiatives. The current trends in the field are also discussed, leading to the need of the present research.

Smart electricity networks based on large integration of renewable sources and distributed generation

Das Grünbuch 2006 der Europäischen Kommission "Eine Europäische Strategie für nachhaltige, wettbewerbsfähige und sichere Energie" unterstreicht, dass Europa in ein neues Energie-Zeitalter eingetreten ist. Die vorrangigen Ziele europäischer Energiepolitik müssen Nachhaltigkeit, Wettbewerbsfähigkeit und Versorgungssicherheit sein, wobei sie eine zusammenhängende und logische Menge von Taktiken und Maßnahmen benötigt, um diese Ziele zu erreichen. Die Strommärkte und Verbundnetze Europas bilden das Kernstück unseres Energiesystems und müssen sich weiterentwickeln, um den neuen Anforderungen zu entsprechen. Die europäischen Stromnetze haben die lebenswichtigen Verbindungen zwischen Stromproduzenten und Verbrauchern mit großem Erfolg seit vielen Jahrzehnten gesichert. Die grundlegende Struktur dieser Netze ist entwickelt worden, um die Bedürfnisse großer, überwiegend auf Kohle aufgebauten Herstellungstechnologien zu befriedigen, die sich entfernt von den Verbraucherzentren befinden. Die Energieprobleme, denen Europa jetzt gegenübersteht, ändern die Stromerzeugungslandschaft in zwei Gesichtspunkten: die Notwendigkeit für saubere Kraftwerkstechnologien verbunden mit erheblich verbesserten Wirkungsgraden auf der Verbraucherseite wird es Kunden ermöglichen, mit den Netzen viel interaktiver zu arbeiten; andererseits müssen die zukünftigen europaweiten Stromnetze allen Verbrauchern eine höchst zuverlässige, preiswerte Energiezufuhr bereitstellen, wobei sowohl die Nutzung von großen zentralisierten Kraftwerken als auch kleineren lokalen Energiequellen überall in Europa ausgeschöpft werden müssen. In diesem Zusammenhang wird darauf hingewiesen, dass die Informationen, die in dieser Arbeit dargestellt werden, auf aktuellen Fragen mit großem Einfluss auf die gegenwärtigen technischen und wirtschaftspolitischen Diskussionen basieren. Der Autor hat während der letzten Jahre viele der hier vorgestellten Schlussfolgerungen und Empfehlungen mit Vertretern der Kraftwerksindustrie, Betreibern von Stromnetzen und Versorgungsbetrieben, Forschungsgremien und den Regulierungsstellen diskutiert. Die folgenden Absätze fassen die Hauptergebnisse zusammen: Diese Arbeit definiert das neue Konzept, das auf mehr verbraucherorientierten Netzen basiert, und untersucht die Notwendigkeiten sowie die Vorteile und die Hindernisse für den Übergang auf ein mögliches neues Modell für Europa: die intelligenten Stromnetze basierend auf starker Integration erneuerbarer Quellen und lokalen Kleinkraftwerken. Das neue Modell wird als eine grundlegende Änderung dargestellt, die sich deutlich auf Netzentwurf und -steuerung auswirken wird. Sie fordert ein europäisches Stromnetz mit den folgenden Merkmalen: – Flexibel: es erfüllt die Bedürfnisse der Kunden, indem es auf Änderungen und neue Forderungen eingehen kann – Zugänglich: es gestattet den Verbindungszugang aller Netzbenutzer besonders für erneuerbare Energiequellen und lokale Stromerzeugung mit hohem Wirkungsgrad sowie ohne oder mit niedrigen Kohlendioxidemissionen – Zuverlässig: es verbessert und garantiert die Sicherheit und Qualität der Versorgung mit den Forderungen des digitalen Zeitalters mit Reaktionsmöglichkeiten gegen Gefahren und Unsicherheiten – Wirtschaftlich: es garantiert höchste Wirtschaftlichkeit durch Innovation, effizientes Energiemanagement und liefert „gleiche Ausgangsbedingungen“ für Wettbewerb und Regulierung. Es beinhaltet die neuesten Technologien, um Erfolg zu gewährleisten, während es die Flexibilität behält, sich an weitere Entwicklungen anzupassen und fordert daher ein zuversichtliches Programm für Forschung, Entwicklung und Demonstration, das einen Kurs im Hinblick auf ein Stromversorgungsnetz entwirft, welches die Bedürfnisse der Zukunft Europas befriedigt: – Netztechnologien, die die Stromübertragung verbessern und Energieverluste verringern, werden die Effizienz der Versorgung erhöhen, während neue Leistungselektronik die Versorgungsqualität verbessern wird. Es wird ein Werkzeugkasten erprobter technischer Lösungen geschaffen werden, der schnell und wirtschaftlich eingesetzt werden kann, so dass bestehende Netze Stromeinleitungen von allen Energieressourcen aufnehmen können. – Fortschritte bei Simulationsprogrammen wird die Einführung innovativer Technologien in die praktische Anwendung zum Vorteil sowohl der Kunden als auch der Versorger stark unterstützen. Sie werden das erfolgreiche Anpassen neuer und alter Ausführungen der Netzkomponenten gewährleisten, um die Funktion von Automatisierungs- und Regelungsanordnungen zu garantieren. – Harmonisierung der ordnungspolitischen und kommerziellen Rahmen in Europa, um grenzüberschreitenden Handel von sowohl Energie als auch Netzdienstleistungen zu erleichtern; damit muss eine Vielzahl von Einsatzsituationen gewährleistet werden. Gemeinsame technische Normen und Protokolle müssen eingeführt werden, um offenen Zugang zu gewährleisten und den Einsatz der Ausrüstung eines jeden Herstellers zu ermöglichen. – Entwicklungen in Nachrichtentechnik, Mess- und Handelssystemen werden auf allen Ebenen neue Möglichkeiten eröffnen, auf Grund von Signalen des Marktes frühzeitig technische und kommerzielle Wirkungsgrade zu verbessern. Es wird Unternehmen ermöglichen, innovative Dienstvereinbarungen zu benutzen, um ihre Effizienz zu verbessern und ihre Angebote an Kunden zu vergrößern. Schließlich muss betont werden, dass für einen erfolgreichen Übergang zu einem zukünftigen nachhaltigen Energiesystem alle relevanten Beteiligten involviert werden müssen.

Effect of dressing on high-order harmonic generation in vibrating H2 molecules

Wir entwickeln die Starkfeldnäherung für die Erzeugung hoher Harmonischer in Wasserstoffmolekülen, wobei die Vibrationsbewegung berücksichtigt wird, sowie die laserinduzierte Kopplung zwischen den beiden untersten Born-Oppenheimer-Zuständen im Molekülion, das durch die anfängliche Ionisation des Moleküls erzeugt wird. Wir zeigen, dass die Kopplung bei längeren Laserwellenlängen (≈ 2 μm) wichtig wird und zu einer Reduzierung der Erzeugung von Harmonischen führt, sowie zu einer Änderung des Verhältnisses von Harmonischen in verschiedenen Isotopen. ----------------------------------------------------------------------- We develop the strong-field approximation for high-order harmonic generation in hydrogen molecules, including the vibrational motion and the laser-induced coupling of the lowest two Born-Oppenheimer states in the molecular ion that is created by the initial ionization of the molecule. We show that the field dressing becomes important at long laser wavelengths (≈ 2 μm), leading to an overall reduction of harmonic generation and modifying the ratio of harmonic signals from different isotopes.

Second Generation Pakistanis in the UK from 1994 to 2005

In spite of being the second largest immigrant group in the United Kingdom, Pakistanis are still one of the most disadvantaged immigrant groups with respect to labour market integration. Hence, dealing with their labour market integration is the first step to improve it. This paper compares second generation Pakistanis in the United Kingdom with their British peers and analyses, whether the gap between the two ethnicities with respect to labour market integration decreased or not. Both groups in the analysis were born in the United Kingdom and possess British nationality. The only difference is the ethnicity; while Pakistanis have Pakistani ethnicity; British people have “white” ethnicity. The analysis covers people whose age are between 18 and 33 years old and compares the time period of December 1993-February 1995 and December 2004-February 2006. To carry out this analysis, I operationalise labour market integration as employment chance and utilise the United Kingdom Quarterly Labour Force Survey data. Empirical findings show that the gap between the labour market integration of second generation Pakistanis and their British peers in the sample did not change significantly from 1994 to 2005.

Master Plan for Renewable Energy based Electricity Generation in The Gambia

The principal objective of this paper is to develop a methodology for the formulation of a master plan for renewable energy based electricity generation in The Gambia, Africa. Such a master plan aims to develop and promote renewable sources of energy as an alternative to conventional forms of energy for generating electricity in the country. A tailor-made methodology for the preparation of a 20-year renewable energy master plan focussed on electricity generation is proposed in order to be followed and verified throughout the present dissertation, as it is applied for The Gambia. The main input data for the proposed master plan are (i) energy demand analysis and forecast over 20 years and (ii) resource assessment for different renewable energy alternatives including their related power supply options. The energy demand forecast is based on a mix between Top-Down and Bottom-Up methodologies. The results are important data for future requirements of (primary) energy sources. The electricity forecast is separated in projections at sent-out level and at end-user level. On the supply side, Solar, Wind and Biomass, as sources of energy, are investigated in terms of technical potential and economic benefits for The Gambia. Other criteria i.e. environmental and social are not considered in the evaluation. Diverse supply options are proposed and technically designed based on the assessed renewable energy potential. This process includes the evaluation of the different available conversion technologies and finalizes with the dimensioning of power supply solutions, taking into consideration technologies which are applicable and appropriate under the special conditions of The Gambia. The balance of these two input data (demand and supply) gives a quantitative indication of the substitution potential of renewable energy generation alternatives in primarily fossil-fuel-based electricity generation systems, as well as fuel savings due to the deployment of renewable resources. Afterwards, the identified renewable energy supply options are ranked according to the outcomes of an economic analysis. Based on this ranking, and other considerations, a 20-year investment plan, broken down into five-year investment periods, is prepared and consists of individual renewable energy projects for electricity generation. These projects included basically on-grid renewable energy applications. Finally, a priority project from the master plan portfolio is selected for further deeper analysis. Since solar PV is the most relevant proposed technology, a PV power plant integrated to the fossil-fuel powered main electrical system in The Gambia is considered as priority project. This project is analysed by economic competitiveness under the current conditions in addition to sensitivity analysis with regard to oil and new-technology market conditions in the future.

Impact of sward type, cutting date and conditioning temperature on mass and energy flows in the integrated generation of solid fuel and biogas from semi-natural grassland

Energy production from biomass and the conservation of ecologically valuable grassland habitats are two important issues of agriculture today. The combination of a bioenergy production, which minimises environmental impacts and competition with food production for land with a conversion of semi-natural grasslands through new utilization alternatives for the biomass, led to the development of the IFBB process. Its basic principle is the separation of biomass into a liquid fraction (press fluid, PF) for the production of electric and thermal energy after anaerobic digestion to biogas and a solid fraction (press cake, PC) for the production of thermal energy through combustion. This study was undertaken to explore mass and energy flows as well as quality aspects of energy carriers within the IFBB process and determine their dependency on biomass-related and technical parameters. Two experiments were conducted, in which biomass from semi-natural grassland was conserved as silage and subjected to a hydrothermal conditioning and a subsequent mechanical dehydration with a screw press. Methane yield of the PF and the untreated silage was determined in anaerobic digestion experiments in batch fermenters at 37°C with a fermentation time of 13-15 and 27-35 days for the PF and the silage, respectively. Concentrations of dry matter (DM), ash, crude protein (CP), crude fibre (CF), ether extract (EE), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent ligning (ADL) and elements (K, Mg, Ca, Cl, N, S, P, C, H, N) were determined in the untreated biomass and the PC. Higher heating value (HHV) and ash softening temperature (AST) were calculated based on elemental concentration. Chemical composition of the PF and mass flows of all plant compounds into the PF were calculated. In the first experiment, biomass from five different semi-natural grassland swards (Arrhenaterion I and II, Caricion fuscae, Filipendulion ulmariae, Polygono-Trisetion) was harvested at one late sampling (19 July or 31 August) and ensiled. Each silage was subjected to three different temperature treatments (5°C, 60°C, 80°C) during hydrothermal conditioning. Based on observed methane yields and HHV as energy output parameters as well as literature-based and observed energy input parameters, energy and green house gas (GHG) balances were calculated for IFBB and two reference conversion processes, whole-crop digestion of untreated silage (WCD) and combustion of hay (CH). In the second experiment, biomass from one single semi-natural grassland sward (Arrhenaterion) was harvested at eight consecutive dates (27/04, 02/05, 09/05, 16/05, 24/05, 31/05, 11/06, 21/06) and ensiled. Each silage was subjected to six different treatments (no hydrothermal conditioning and hydrothermal conditioning at 10°C, 30°C, 50°C, 70°C, 90°C). Energy balance was calculated for IFBB and WCD. Multiple regression models were developed to predict mass flows, concentrations of elements in the PC, concentration of organic compounds in the PF and energy conversion efficiency of the IFBB process from temperature of hydrothermal conditioning as well as NDF and DM concentration in the silage. Results showed a relative reduction of ash and all elements detrimental for combustion in the PC compared to the untreated biomass of 20-90%. Reduction was highest for K and Cl and lowest for N. HHV of PC and untreated biomass were in a comparable range (17.8-19.5 MJ kg-1 DM), but AST of PC was higher (1156-1254°C). Methane yields of PF were higher compared to those of WCD when the biomass was harvested late (end of May and later) and in a comparable range when the biomass was harvested early and ranged from 332 to 458 LN kg-1 VS. Regarding energy and GHG balances, IFBB, with a net energy yield of 11.9-14.1 MWh ha-1, a conversion efficiency of 0.43-0.51, and GHG mitigation of 3.6-4.4 t CO2eq ha-1, performed better than WCD, but worse than CH. WCD produces thermal and electric energy with low efficiency, CH produces only thermal energy with a low quality solid fuel with high efficiency, IFBB produces thermal and electric energy with a solid fuel of high quality with medium efficiency. Regression models were able to predict target parameters with high accuracy (R2=0.70-0.99). The influence of increasing temperature of hydrothermal conditioning was an increase of mass flows, a decrease of element concentrations in the PC and a differing effect on energy conversion efficiency. The influence of increasing NDF concentration of the silage was a differing effect on mass flows, a decrease of element concentrations in the PC and an increase of energy conversion efficiency. The influence of increasing DM concentration of the silage was a decrease of mass flows, an increase of element concentrations in the PC and an increase of energy conversion efficiency. Based on the models an optimised IFBB process would be obtained with a medium temperature of hydrothermal conditioning (50°C), high NDF concentrations in the silage and medium DM concentrations of the silage.