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.

A Hybrid Architecture for Recognising Speech Signals in Malayalam

Speech is the primary, most prominent and convenient means of communication in audible language. Through speech, people can express their thoughts, feelings or perceptions by the articulation of words. Human speech is a complex signal which is non stationary in nature. It consists of immensely rich information about the words spoken, accent, attitude of the speaker, expression, intention, sex, emotion as well as style. The main objective of Automatic Speech Recognition (ASR) is to identify whatever people speak by means of computer algorithms. This enables people to communicate with a computer in a natural spoken language. Automatic recognition of speech by machines has been one of the most exciting, significant and challenging areas of research in the field of signal processing over the past five to six decades. Despite the developments and intensive research done in this area, the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level. The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam.

Towards Realization of Magnetocaloric and Magnetoelectric Applications based on Bulk and Thin film forms of Sodium substituted Lanthanum Manganites

The present thesis work focuses on hole doped lanthanum manganites and their thin film forms. Hole doped lanthanum manganites with higher substitutions of sodium are seldom reported in literature. Such high sodium substituted lanthanum manganites are synthesized and a detailed investigation on their structural and magnetic properties is carried out. Magnetic nature of these materials near room temperature is investigated explicitly. Magneto caloric application potential of these materials are also investigated. After a thorough investigation of the bulk samples, thin films of the bulk counterparts are also investigated. A magnetoelectric composite with ferroelectric and ferromagnetic components is developed using pulsed laser deposition and the variation in the magnetic and electric properties are investigated. It is established that such a composite could be realized as a potential field effect device. The central theme of this thesis is also on manganites and is with the twin objectives of a material study leading to the demonstration of a device. This is taken up for investigation. Sincere efforts are made to synthesize phase pure compounds. Their structural evaluation, compositional verification and evaluation of ferroelectric and ferromagnetic properties are also taken up. Thus the focus of this investigation is related to the investigation of a magnetoelectric and magnetocaloric application potentials of doped lanthanum manganites with sodium substitution. Bulk samples of sodium substituted lanthanum manganites. Bulk samples of sodium substituted lanthanum manganites with Na substitution ranging from 50 percent to 90 percent were synthesized using a modified citrate gel method and were found to be orthorhombic in structure belonging to a pbnm spacegroup. The variation in lattice parameters and unit cell volume with sodium concentration were also dealt with. Magnetic measurements revealed that magnetization decreased with increase in sodium concentrations.

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.