Fractal based techniques for classification of mammograms and identification of microcalcifications

After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

Classification of Mammograms and DW T based Detection of Microcalcification

Cancer treatment is most effective when it is detected early and the progress in treatment will be closely related to the ability to reduce the proportion of misses in the cancer detection task. The effectiveness of algorithms for detecting cancers can be greatly increased if these algorithms work synergistically with those for characterizing normal mammograms. This research work combines computerized image analysis techniques and neural networks to separate out some fraction of the normal mammograms with extremely high reliability, based on normal tissue identification and removal. The presence of clustered microcalcifications is one of the most important and sometimes the only sign of cancer on a mammogram. 60% to 70% of non-palpable breast carcinoma demonstrates microcalcifications on mammograms [44], [45], [46].WT based techniques are applied on the remaining mammograms, those are obviously abnormal, to detect possible microcalcifications. The goal of this work is to improve the detection performance and throughput of screening-mammography, thus providing a ‘second opinion ‘ to the radiologists. The state-of- the- art DWT computation algorithms are not suitable for practical applications with memory and delay constraints, as it is not a block transfonn. Hence in this work, the development of a Block DWT (BDWT) computational structure having low processing memory requirement has also been taken up.

Classification of Handwritten Characters: Definition, Identification and Utilisation of Regional Characteristics for Lower Case English Characters

A new procedure for the classification of lower case English language characters is presented in this work . The character image is binarised and the binary image is further grouped into sixteen smaller areas ,called Cells . Each cell is assigned a name depending upon the contour present in the cell and occupancy of the image contour in the cell. A data reduction procedure called Filtering is adopted to eliminate undesirable redundant information for reducing complexity during further processing steps . The filtered data is fed into a primitive extractor where extraction of primitives is done . Syntactic methods are employed for the classification of the character . A decision tree is used for the interaction of the various components in the scheme . 1ike the primitive extraction and character recognition. A character is recognized by the primitive by primitive construction of its description . Openended inventories are used for including variants of the characters and also adding new members to the general class . Computer implementation of the proposal is discussed at the end using handwritten character samples . Results are analyzed and suggestions for future studies are made. The advantages of the proposal are discussed in detail .

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

Studies on the isolation and characterization of flavones and triterpenoids from a few plants

In the present scenario, there is an increasing demand for natural products in food industry, pharmaceuticals, cosmetics and agricultural sectors. In this context phytochemical study to identify newer chemicals has got great relevance. Phytochemical studies have become more reliable and encouraging with the development of modern analytical techniques.In the present work the leaves of Piper colubrinum (Piperaceae), aerial parts of Mussaenda fiondosa (Rubiaceae) and Humboldtia vahliana (Leguminosae) and the pericarp of fruits of Artocarpus heterophyllus (Moraceae) were investigated for their secondary metabolites. The major compounds isolated belong to the groups of flavonoids and triterpenoids.Naturally occurring flavonoids have been used widely in chemotaxonomic studies of plants. Flavones and flavonols constitute a group of biosynthetically related natural products. No universal function has been established for flavones and flavonols in plants. However, many functions in individual plants have been demonstrated. These include protection of plants from ultraviolet light, insects and pests; pollinator attractants; antioxidants; plant hormone controllers; enzyme inhibitors and allelopathic agents. Flavonoids are attracting the attention of medical scientists in recent years because of their anticarcinogenic, antiallergic and antiinflammatory properties. The recent discovery that flavonoids are involved in the process of nitrogen fixation in plants also opens the way for agricultural application of these constituents.Triterpenoids are another class of compounds that are ubiquitous in plants. Some triterpenoids present in the latex and resins of plants are believed to be involved in chemical defence against pathogens and herbivores. Triterpenoids possess various biological properties including anti-inflammatory, antifeedant, pesticidal, fungitoxic and antimicrobial activities. Triterpenoids with cytotoxic activity and inhibitory effect on seed germination are also known.

Fish habitats and species assemblage in the selected rivers of Kerala and investigation on life history traits of Puntius carnaticus(Jerdon,1849)

This thesis entitled Fish habitats and species assemblage in the selected rivers of kerala and investigation on life history traits of puntius carnaticus (JERDON,1849). Ecology is a new and exceedingly complex field of study, even though its concept was recognized by the Apostles in their use of the phrase ‘all flesh is grass.central role to play both in order to understand better the biodiversity phenomenon and to be able to draw up clear guidelines for careful resource management. In a review by WWF, IUCN and UNEP on the ways of conserving genetic diversity of freshwater fish it was recommended that the best way to conserve species diversity is to conserve habitat.The habitat studies in freshwater ecosystems are very essential for the proper understanding and management of human impact on fish diversity, to study the relationship between habitat variables and fish species assemblage structure, quantification of ecosystem degradation, habitat quality and biotic integrity of the ecosystems, development of habitat suitability index (I-ISI) models and classification of river reaches based on their physico-chemical properties. Therefore in the present study an attempt was made to assess the biodiversity potential and the relationship between habitat variables and fish species assemblage structure in six major river systems of Kerala which would be very useful in impressing upon the seriousness of habitat degradIn the present study, in Kabbini river system 15 locations encompassing between 721 946m above MSL were surveyed.ation and biotic devastation undergone in the major river systems of Kerala.During the present study the Habitat Quality Score (HQ) developed by the Ohio EPA was applied for the first time in India.The result of the present study revealed that, among various variables analysed, altitude has a very significant influence in deciding the fish diversity in six major river systems of Kerala. The fish diversity studied on the basis of Shanon-Weiner and Simpson diversity indices revealed that even though some minor variations occur with the suitability and complexity of habitats, the altitude showed inverse relationship with fish diversity.The present study revealed that the National Policy on the interlinking of rivers would permanently alter the HSI indices of the above mentioned fish species, which are now solely protected by the individuality of the rivers where their limited occurrence was notice.

Bionomics, cryopreservation of gametes and captive breeding behaviour of threatened hillstream cyprinid, garra surendranathanii(shaji, arun & easa, 1996)

Garra surendranathanii is a hill stream cyprinid endemic to Kerala. According to IUCN based classification, G. surendranathanii is grouped under the threatened category. This endemic fish is having highly restricted and fragmented distribution and reported only from 5 river systems viz. Chalakudy, Periyar, Pamba, Achenkoil and Bharathapuzha. Categorization of this fish as a potential ornamental candidate can invariably add more pressure on the threat status of this particular species. Hence, this species is considered as one which requires foremost attention for conservation. Hitherto, no infomiation is available on the bionomics, resource characteristics and any conservation attempts of G. surendranathanii. Studies on detailed life history traits and development of captive breeding technique are indispensable for successful fishery management.The present study was undertaken with the following obj ectives: To study the Length-weight relationship and condition factor to ascertain the relationship between length and weight and general wellbeing ofthe fish To study the age and growth to understand the age composition of the exploited stock, age at first maturation and life span of the species. To study the reproductive biology of G. surendranathanii to gain insights in the process of gametogenesis, spawning, sex ratio, fecundity and other related aspects which are essential for developing captive breeding technology of this species. To develop captive breeding technology and cryopreservation ofgametes of G. surendranathanii for conservation

“A comparative study of medium and large pore zeolites in alkylation reactions”

Zeolites have established themselves as industrial catalysts for over two decades for a variety of hydrocarbon processing reactions where acidity and shape selectivity are important factors. As solid catalysts, zeolites may be advantageous and superior compared to their homogenous counterparts due to their characteristic properties. It is only in recent years that the utility of zeolites for organic synthesis is recognized for producing specific organic intermediates and fine chemicals in high selectivity. In this thesis an attempt has been made to compare the catalytic activity of some medium and large pore zeolites in a few alkylation and acylation reactions. The work reported in the present study is basically centered around the following zeolites namely, ZSM-5, mordenite, zeolite Y and beta. The major reactions carried out were benzoylation of o-xylene, propionylation of toluene and anisole and benzylation of oxylene. . The programme involves the synthesis, modifications and characterization of the zeolite catalysts by various methods. The influence of various parameters such as non-framework cations, Si/Al ratio of zeolites, temperature of the reaction, catalyst concentration, molar ratio of the reactants and recycling of the catalysts were also examined upon the conversion of reactants and the formation of the desired products in the alkylation/ acylation reactions. The general conclusions drawn by us from the results obtained are summarized in the last chapter of the thesis. Zeolite beta ofi'ers interesting opportunities as a potential catalyst in alkylation reactions and the area of catalysis by medium and large pore zeolites is very fascinating and there is plenty of scope for further research in this field. Moreover, zeolite based catalysts are effective in meeting current industrial processing and more stringent environment pollution limits.

A Classification of Sandhi Rules for Suffix Separation in Malayalam

Suffix separation plays a vital role in improving the quality of training in the Statistical Machine Translation from English into Malayalam. The morphological richness and the agglutinative nature of Malayalam make it necessary to retrieve the root word from its inflected form in the training process. The suffix separation process accomplishes this task by scrutinizing the Malayalam words and by applying sandhi rules. In this paper, various handcrafted rules designed for the suffix separation process in the English Malayalam SMT are presented. A classification of these rules is done based on the Malayalam syllable preceding the suffix in the inflected form of the word (check_letter). The suffixes beginning with the vowel sounds like ആല, ഉെെ, ഇല etc are mainly considered in this process. By examining the check_letter in a word, the suffix separation rules can be directly applied to extract the root words. The quick look up table provided in this paper can be used as a guideline in implementing suffix separation in Malayalam language

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.