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.

Morphological filtering on hypergraphs

The focus of this article is to develop computationally efficient mathematical morphology operators on hypergraphs. To this aim we consider lattice structures on hypergraphs on which we build morphological operators. We develop a pair of dual adjunctions between the vertex set and the hyper edge set of a hypergraph H, by defining a vertex-hyperedge correspondence. This allows us to recover the classical notion of a dilation/erosion of a subset of vertices and to extend it to subhypergraphs of H. Afterward, we propose several new openings, closings, granulometries and alternate sequential filters acting (i) on the subsets of the vertex and hyperedge set of H and (ii) on the subhypergraphs of a hypergraph

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

A study on semigroup action on fuzzy subsets, inverse fuzzy automata and related topics

This thesis comprises five chapters including the introductory chapter. This includes a brief introduction and basic definitions of fuzzy set theory and its applications, semigroup action on sets, finite semigroup theory, its application in automata theory along with references which are used in this thesis. In the second chapter we defined an S-fuzzy subset of X with the extension of the notion of semigroup action of S on X to semigroup action of S on to a fuzzy subset of X using Zadeh's maximal extension principal and proved some results based on this. We also defined an S-fuzzy morphism between two S-fuzzy subsets of X and they together form a category S FSETX. Some general properties and special objects in this category are studied and finally proved that S SET and S FSET are categorically equivalent. Further we tried to generalize this concept to the action of a fuzzy semigroup on fuzzy subsets. As an application, using the above idea, we convert a _nite state automaton to a finite fuzzy state automaton. A classical automata determine whether a word is accepted by the automaton where as a _nite fuzzy state automaton determine the degree of acceptance of the word by the automaton. 1.5. Summary of the Thesis 17 In the third chapter we de_ne regular and inverse fuzzy automata, its construction, and prove that the corresponding transition monoids are regular and inverse monoids respectively. The languages accepted by an inverse fuzzy automata is an inverse fuzzy language and we give a characterization of an inverse fuzzy language. We study some of its algebraic properties and prove that the collection IFL on an alphabet does not form a variety since it is not closed under inverse homomorphic images. We also prove some results based on the fact that a semigroup is inverse if and only if idempotents commute and every L-class or R-class contains a unique idempotent. Fourth chapter includes a study of the structure of the automorphism group of a deterministic faithful inverse fuzzy automaton and prove that it is equal to a subgroup of the inverse monoid of all one-one partial fuzzy transformations on the state set. In the fifth chapter we define min-weighted and max-weighted power automata study some of its algebraic properties and prove that a fuzzy automaton and the fuzzy power automata associated with it have the same transition monoids. The thesis ends with a conclusion of the work done and the scope of further study.

Synthesis and Photoluminescence Properties of Novel Red Phosphors for White Light Emitting Diode Applications

Several series of Eu3+ based red emitting phosphor materials were synthesized using solid state reaction route and their properties were characterized. The present studies primarily investigated the photoluminescence properties of Eu3+ in a family of closely related host structure with a general formula Ln3MO7. The results presented in the previous chapters throws light to a basic understanding of the structure, phase formation and the photoluminescence properties of these compounds and their co-relations. The variation in the Eu3+ luminescence properties with different M cations was studied in Gd3-xMO7 (M = Nb, Sb, Ta) system.More ordering in the host lattice and more uniform distribution of Eu3+ ions resulting in the increased emission properties were observed in tantalate system.Influence of various lanthanide ion (Lu, Y, Gd, La) substitutions on the Eu3+ photoluminescence properties in Ln3MO7 host structures was also studied. The difference in emission profiles with different Ln ions demonstrated the influence of long range ordering, coordination of cations and ligand polarizability in the emission probabilities, intensity and quantum efficiency of these phosphor materials. Better luminescence of almost equally competing intensities from all the 4f transitions of Eu3+ was noticed for La3TaO7 system. Photoluminescence properties were further improved in La3TaO7 : Eu3+ phosphors by the incorporation of Ba2+ ions in La3+ site. New red phosphor materials Gd2-xGaTaO7 : xEu3+ exhibiting intense red emissions under UV excitation were prepared. Optimum doping level of Eu3+ in these different host lattices were experimentally determined. Some of the prepared samples exhibited higher emission intensities than the standard Y2O3 : Eu3+ red phosphors. In the present studies, Eu3+ acts as a structural probe determining the coordination and symmetry of the atoms in the host lattice. Results from the photoluminescence studies combined with the powder XRD and Raman spectroscopy investigations helped in the determination of the correct crystal structures and phase formation of the prepared compounds. Thus the controversy regarding the space groups of these compounds could be solved to a great extent. The variation in the space groups with different cation substitutions were discussed. There was only limited understanding regarding the various influential parameters of the photoluminescence properties of phosphor materials. From the given studies, the dependence of photoluminescence properties on the crystal structure and ordering of the host lattice, site symmetries, polarizability of the ions, distortions around the activator ion, uniformity in the activator distribution, concentration of the activator ion etc. were explained. Although the presented work does not directly evidence any application, the materials developed in the studies can be used for lighting applications together with other components for LED lighting. All the prepared samples were well excitable under near UV radiation. La3TaO7 : 0.15Eu3+ phosphor with high efficiency and intense orange red emissions can be used as a potential red component for the realization of white light with better color rendering properties. Gd2GaTaO7 : Eu3+, Bi2+ red phosphors give good color purity matching to NTSC standards of red. Some of these compounds exhibited higher emission intensities than the standard Y2O3 : Eu3+ red phosphors. However thermal stability and electrical output using these compounds should be studied further before applications. Based on the studies in the closely related Ln3MO7 structures, some ideas on selecting better host lattice for improved luminescence properties could be drawn. Analyzing the CTB position and the number of emission splits, a general understanding on the doping sites can be obtained. These results could be helpful for phosphor designs in other host systems also, for enhanced emission intensity and efficiency.