Detection of microcalcifications in mammograms using local maxima andadaptive wavelet transform analysis

A method for computer- aided diagnosis of micro calcification clusters in mammograms images presented . Micro calcification clus.eni which are an early sign of bread cancer appear as isolated bright spots in mammograms. Therefore they correspond to local maxima of the image. The local maxima of the image is lint detected and they are ranked according to it higher-order statistical test performed over the sub band domain data

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

Artificial neural network modeling for surface roughness prediction in cylindrical grinding of Al‐SiCp metal matrix composites and ANOVA analysis

Metal matrix composites (MMC) having aluminium (Al) in the matrix phase and silicon carbide particles (SiCp) in reinforcement phase, ie Al‐SiCp type MMC, have gained popularity in the re‐cent past. In this competitive age, manufacturing industries strive to produce superior quality products at reasonable price. This is possible by achieving higher productivity while performing machining at optimum combinations of process variables. The low weight and high strength MMC are found suitable for variety of components

Plasma Polymerised Organic Thin Films-A Study on the Structural, Electrical and Nonlinear Optical Properties for Possible Applications

This proposed thesis is entitled “Plasma Polymerised Organic Thin Films: A study on the Structural, Electrical, and Nonlinear Optical Properties for Possible Applications. Polymers and polymer based materials find enormous applications in the realm of electronics and optoelectronics. They are employed as both active and passive components in making various devices. Enormous research activities are going on in this area for the last three decades or so, and many useful contributions are made quite accidentally. Conducting polymers is such a discovery, and eversince the discovery of conducting polyacetylene, a new branch of science itself has emerged in the form of synthetic metals. Conducting polymers are useful materials for many applications like polymer displays, high density data storage, polymer FETs, polymer LEDs, photo voltaic devices and electrochemical cells. With the emergence of molecular electronics and its potential in finding useful applications, organic thin films are receiving an unusual attention by scientists and engineers alike. This is evident from the vast literature pertaining to this field appearing in various journals. Recently, computer aided design of organic molecules have added further impetus to the ongoing research activities in this area. Polymers, especially, conducting polymers can be prepared both in the bulk and in the thinfilm form. However, many applications necessitate that they are grown in the thin film form either as free standing or on appropriate substrates. As far as their bulk counterparts are concerned, they can be prepared by various polymerisation techniques such as chemical routes and electrochemical means. A survey of the literature reveals that polymers like polyaniline, polypyrrole, polythiophene, have been investigated with a view to studying their structural electrical and optical properties. Among the various alternate techniques employed for the preparation of polymer thin films, the method of plasma polymerisation needs special attention in this context. The technique of plasma polymerisation is an inexpensive method and often requires very less infra structure. This method includes the employment of ac, rf, dc, microwave and pulsed sources. They produce pinhole free homogeneous films on appropriate substrates under controlled conditions. In conventional plasma polymerisation set up, the monomer is fed into an evacuated chamber and an ac/rf/dc/ w/pulsed discharge is created which enables the monomer species to dissociate, leading to the formation of polymer thin films. However, it has been found that the structure and hence the properties exhibited by plasma polymerized thin films are quite different from that of their counterparts produced by other thin film preparation techniques such as electrochemical deposition or spin coating. The properties of these thin films can be tuned only if the interrelationship between the structure and other properties are understood from a fundamental point of view. So very often, a through evaluation of the various properties is a pre-requisite for tailoring the properties of the thin films for applications. It has been found that conjugation is a necessary condition for enhancing the conductivity of polymer thin films. RF technique of plasma polymerisation is an excellent tool to induce conjugation and this modifies the electrical properties too. Both oxidative and reductive doping can be employed to modify the electrical properties of the polymer thin films for various applications. This is where organic thin films based on polymers scored over inorganic thin films, where in large area devices can be fabricated with organic semiconductors which is difficult to achieve by inorganic materials. For such applications, a variety of polymers have been synthesized such as polyaniline, polythiophene, polypyrrole etc. There are newer polymers added to this family every now and then. There are many virgin areas where plasma polymers are yet to make a foray namely low-k dielectrics or as potential nonlinear optical materials such as optical limiters. There are also many materials which are not been prepared by the method of plasma polymerisation. Some of the materials which are not been dealt with are phenyl hydrazine and tea tree oil. The advantage of employing organic extracts like tea tree oil monomers as precursors for making plasma polymers is that there can be value addition to the already existing uses and possibility exists in converting them to electronic grade materials, especially semiconductors and optically active materials for photonic applications. One of the major motivations of this study is to synthesize plasma polymer thin films based on aniline, phenyl hydrazine, pyrrole, tea tree oil and eucalyptus oil by employing both rf and ac plasma polymerisation techniques. This will be carried out with the objective of growing thin films on various substrates such as glass, quartz and indium tin oxide (ITO) coated glass. There are various properties namely structural, electrical, dielectric permittivity, nonlinear optical properties which are to be evaluated to establish the relationship with the structure and the other properties. Special emphasis will be laid in evaluating the optical parameters like refractive index (n), extinction coefficient (k), the real and imaginary components of dielectric constant and the optical transition energies of the polymer thin films from the spectroscopic ellipsometric studies. Apart from evaluating these physical constants, it is also possible to predict whether a material exhibit nonlinear optical properties by ellipsometric investigations. So further studies using open aperture z-scan technique in order to evaluate the nonlinear optical properties of a few selected samples which are potential nonlinear optical materials is another objective of the present study. It will be another endeavour to offer an appropriate explanation for the nonlinear optical properties displayed by these films. Doping of plasma polymers is found to modify both the electrical conductivity and optical properties. Iodine is found to modify the properties of the polymer thin films. However insitu iodine doping is tricky and the film often looses its stability because of the escape of iodine. An appropriate insitu technique of doping will be developed to dope iodine in to the plasma polymerized thin films. Doping of polymer thin films with iodine results in improved and modified optical and electrical properties. However it requires tools like FTIR and UV-Vis-NIR spectroscopy to elucidate the structural and optical modifications imparted to the polymer films. This will be attempted here to establish the role of iodine in the modification of the properties exhibited by the films

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 and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images