“Improved Feature Extraction and Classification Techniques for Multispectral Brain Magnetic Resonance Images”

Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.

A Comparative Study of Wavelet Based Feature Extraction Techniques in Recognizing Isolated Spoken Words

Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech

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.

Potential application of β-1, 3 glucanase from an environmental isolate of Pseudomonas aeruginosa MCCB 123 in fungal DNA extraction

Pseudomonas aeruginosa MCCB 123 was grown in a synthetic medium for β-1,3 glucanase production. From the culture filtrate, β-1,3 glucanase was purified with a molecular mass of 45 kDa. The enzyme was a metallozyme as its β-1,3 glucanase activity got inhibited by the metal chelator EDTA. Optimum pH and temperature for β-1,3 glucanase activity on laminarin was found to be 7 and 50 °C respectively. The MCCB 123 β-1,3 glucanase was found to have good lytic action on a wide range of fungal isolates, and hence its application in fungal DNA extraction was evaluated. β-1,3 glucanase purified from the culture supernatant of P. aeruginosa MCCB 123 could be used for the extraction of fungal DNA without the addition of any other reagents generally used. Optimum pH and temperature of enzyme for fungal DNA extraction was found to be 7 and 65 °C respectively. This is the first report on β-1,3 glucanase employed in fungal DNA extraction

Ontology based Framework for News Extraction in Visual Media

Anticipating the increase in video information in future, archiving of news is an important activity in the visual media industry. When the volume of archives increases, it will be difficult for journalists to find the appropriate content using current search tools. This paper provides the details of the study we conducted about the news extraction systems used in different news channels in Kerala. Semantic web technologies can be used effectively since news archiving share many of the characteristics and problems of WWW. Since visual news archives of different media resources follow different metadata standards, interoperability between the resources is also an issue. World Wide Web Consortium has proposed a draft for an ontology framework for media resource which addresses the intercompatiblity issues. In this paper, the w3c proposed framework and its drawbacks is also discussed

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

The Ratios of Carbon, Nitrogen, and Phosphorus in a Wetland Coastal Ecosystem of Southern India

The fertility of the coastal and estuarine waters is of great concern because of its influence on the productivity of these waters. Seasonal variations in the distribution of organic carbon, total nitrogen and total phosphorus in the sediments of Kuttanad Waters, a part of the tropical Cochin Estuary on the south west coast of India, are examined to identify the contribution of sediments to the fertility of the aquatic systems. The adjoining region has considerable agricultural activity. The fresh water zones had higher quantities of silt and clay whereas the estuarine zone was more sandy. Organic carbon, total phosphorus and total nitrogen were higher in the fresh water zones and lower in the estuarine zones. Total phosphorus and organic carbon showed the lowest values during monsoon periods. No significant trends were observed in the seasonal distributions of total nitrogen. Ratios of C/N, C/P and N/P, and the phosphorus and nitrogen content indicate significant modification in the character of the organic matter. Substantial amounts of the organic matter can contribute to reducing conditions and modify diagenetic processes

Destructive and non-destructive measurements of residual crop residue and phosphorus effects on growth and composition of herbaceous fallow species in the Sahel

Little is known about the residual effects of crop residue (CR) and phosphorus (P) application on the fallow vegetation following repeated cultivation of pearl millet [Pennisetum glaucum (L.) R. Br.] in the Sahel. The objective of this study, therefore, was (i) to measure residual effects of CR, mulched at annual rates of 0, 500, 1000 and 2000 kg CR ha^-1, broadcast P at 0 and 13 kg P ha^-1 and P placement at 0, 1, 3, 5 and 7 kg P ha^-1 on the herbaceous dry matter (HDM) 2 years after the end of the experiment and (ii) to test a remote sensing method for the quantitative estimation of HDM. Compared with unmulched plots, a doubling of HDM was measured in plots that had received at least 500 kg CR ha^-1. Previous broadcast P application led to HDM increases of 14% compared with unfertilised control plots, whereas no residual effects of P placement were detected. Crop residue and P treatments caused significant shifts in flora composition. Digital analysis of colour photographs taken of the fallow vegetation and the bare soil revealed that the number of normalised green band pixels averaged per plot was highly correlated with HDM (r=0.86) and that red band pixels were related to differences in soil surface crusting. Given the traditional use of fallow vegetation as fodder, the results strongly suggest that for the integrated farming systems of the West African Sahel, residual effects of soil amendments on the fallow vegetation should be included in any comprehensive analysis of treatment effects on the agro-pastoral system.

Effects of fertility management strategies on phosphorus bioavailability in four West African soils

Low phosphorus (P) in acid sandy soils of the West African Sudano-Sahelian zone is a major limitation to crop growth. To compare treatment effects on total dry matter (TDM) of crops and plant available P (P-Bray and isotopically exchangeable P), field experiments were carried out for 2 years at four sites where annual rainfall ranged from 560 to 850 mm and topsoil pH varied between 4.2 and 5.6. Main treatments were: (i) crop residue (CR) mulch at 500 and 2000 kg ha^-1, (ii) eight different rates and sources of P and (iii) cereal/legume rotations including millet (Pennisetum glaucum L.), sorhum [Sorghum bicolor (L.) Moench], cowpea (Vigna unguiculata Walp.) and groundnut (Arachis hypogaea L.). For the two Sahelian sites with large CR-induced differences in TDM, mulching did not modify significantly the soils' buffering capacity for phosphate ions but led to large increases in the intensity factor (C_p) and quantity of directly available soil P (E_1min). In the wetter Sudanian zone lacking effects of CR mulching on TDM mirrored a decline of E_1min with CR. Broadcast application of soluble single superphosphate (SSP) at 13 kg P ha^-1 led to large increases in C_p and quantity of E_1min at all sites which translated in respective TDM increases. The high agronomic efficiency of SSP placement (4 kg P ha^-1) across sites could be explained by consistent increases in the quantity factor which confirms the power of the isotopic exchange method in explaining management effects on crop growth across the region.

Efficient phosphorus application strategies for increased crop production in sub-Saharan West Africa

Comparable data are lacking from the range of environments found in sub-Saharan West Africa to draw more general conclusions about the relative merits of locally available rockphosphate (RockP) in alleviating phosphorus (P) constraints to crop growth. To fill this gap, a multi-factorial field experiment was conducted over 4 years at eight locations in Niger, Burkina Faso and Togo. These ranged in annual rainfall from 510 to 1300 mm. Crops grown were pearl millet (Pennisetum glaucum L.), sorghum (Sorghum bicolor (L.) Moench) and maize (Zea mays L.) either continuously or in rotation with cowpea (Vigna unguiculata Walp.) and groundnut (Arachis hypogaea L.). Crops were subjected to six P fertiliser treatments comprising RockP and soluble P at different rates and combined with 0 and 60 kg N ha^-1. For legumes, time trend analyses showed P-induced total dry matter (TDM) increases between 28 and 72% only with groundnut. Similarly, rotation-induced raises in cereal TDM compared to cereal monoculture were only observed with groundnut. For cereals, at the same rate of application, RockP was comparable to single superphosphate (SSP) only at two millet sites with topsoil pH-KCl <4.2 and annual average rainfall >600 mm. Across the eight sites NPK placement at 0.4 g P per hill raised average cereal yields between 26 and 220%. This was confirmed in 119 on-farm trials revealing P placement as a promising strategy to overcome P deficiency as the regionally most growth limiting nutrient constraint to cereals.

Phosphorus placement an acid arenosols of the West African Sahel

Phosphorus (P) deficiency is a major constraint to pearl millet (Pennisetum glaucum L.) growth on acid sandy soils of the West African Sahel. To develop cost-effective fertilization strategies for cash poor farmers, experiments with pearl millet were conducted in southwestern Niger. Treatments comprised single superphosphate hill-placed at rates of 1, 3, 5 or 7 kg P ha^−1 factorially combined with broadcast P at a rate of 13 kg ha^−1. Nitrogen was applied as calcium ammonium nitrate at rates of 30 and 45 kg ha^−1. At low soil moisture, placement of single superphosphate in immediate proximity to the seed reduced seedling emergence. Despite these negative effects on germination, P placement resulted in much faster growth of millet seedlings than did broadcast P. With P application, potassium nutrition of millet was improved and seedling nitrogen uptake increased two- to three-fold, indicating that nitrogen was not limiting early millet growth. Averaged over the 1995 and 1996 cropping seasons, placed applications of 3, 5 and 7 kg P ha^−1 led to 72%, 81% and 88% respectively, of the grain yield produced by broadcasting 13 kg P ha^−1. Nitrogen application did not show major effects on grain yield unless P requirements were met. A simple economic analysis revealed that the profitability of P application, defined as additional income per unit of fertilizer, was highest for P placement at 3 and 5 kg ha^−1.

The electronic structure of anionic halide complexes of element 105 in aqueous solutions and their extraction by aliphatic amines

To study the complex formation of group 5 elements (Nb, Ta, Ha, and pseudoanalog Pa) in aqueous HCI solutions of medium and high concentrations the electronic structures of anionic complexes of these elements [MCl_6]^-, [MOCl_4]^-, [M(OH)-2 Cl_4]^-, and [MOCl_5]^2- have been calculated using the relativistic Dirac-Slater Discrete-Variational Method. The charge density distribution analysis has shown that tantalum occupies a specific position in the group and has the highest tendency to form the pure halide complex, [TaCl_6-. This fact along with a high covalency of this complex explains its good extractability into aliphatic amines. Niobium has equal trends to form pure halide [NbCl_6]^- and oxyhalide [NbOCl_5]^2- species at medium and high acid concentrations. Protactinium has a slight preference for the [PaOCl_5]^2- form or for the pure halide complexes with coordination number higher than 6 under these conditions. Element 105 at high HCl concentrations will have a preference to form oxyhalide anionic complex [HaOCl_5]^2- rather than [HaCl_6]^-. For the same sort of anionic oxychloride complexes an estimate has been done of their partition between the organic and aqueous phases in the extraction by aliphatic amines, which shows the following succession of the partition coefficients: P_Nb < P_Ha < P_Pa.

Effects of phosphorus and water stress on shoot and root growth and on mycorrhization of different pearl millet (Pennisetum glaucum (L.) R. Br.) varieties from West Africa

This research work aimed at investigating the physiological mechanisms of tolerance of pearl millet to low soil Phosphorus availability and drought under the Sahelian conditions.