DETECTION OF BILIARY FUNCTIONAL PROBLEMS USING MICROWAVES

This article reports a new in vitro bile analysis based on the measurement of the dielectric properties at microwave frequencies. The measurements were made using rectangular cavity perturbation technique at the S-band of microwave frequency with the different samples of bile obtained from healthy persons as well as from patients. It is observed that an appreciable change in the dielectric properties of patient’s samples with the normal healthy samples and these measurements were in good agreement with clinical analysis. These results prove an alternative in-vitro method of detecting bile abnormalities based on the measurement of the dielectric properties of bile samples using microwaves without surgical procedure.

HUMAN PERICARDIAL FLUID AT MICROWAVE FREQUENCIES

This article reports a new method of analyzing pericardial fluid based on the measurement of the dielectric properties at microwave frequencies. The microwave measurements were performed by rectangular cavity perturbation method in the S-band of microwave frequency with the pericardial fluid from healthy persons as well as from patients suffering from pericardial effusion. It is observed that a remarkable change in the dielectric properties of patient samples with the normal healthy samples and these measurements were in good agreement with clinical analysis. This measurement technique and the method of extraction of pericardial fluid are simple. These results give light to an alternative in-vitro method of diagnosing onset pericardial effusion abnormalities using microwaves without surgical procedure.

Bone marrow cells differentiation to neurons in the rat brain using Serotonin and GABA:Their role on glutamate receptors, IP3, cAMP and cGMP functional regulation in unilateral Parkinsonism induced by 6-hydroxydopamine

Parkinson's disease is a chronic progressive neurodegenerative movement disorder characterized by a profound and selective loss of nigrostriatal dopaminergic neurons. Our findings demonstrated that glutamatergic system is impaired during PD. The evaluations of these damages have important implications in understanding the molecular mechanism underlying motor, cognitive and memory deficits in PD. Our results showed a significant increase of glutamate content in the brain regions of 6- OHDA infused rat compared to control. This increased glutamate content caused an increase in glutamatergic and NMDA receptors function. Glutamate receptor subtypes- NMDAR1, NMDA2B and mGluR5 have differential regulatory role in different brain regions during PD. The second messenger studies confirmed that the changes in the receptor levels alter the IP3, cAMP and cGMP content. The alteration in the second messengers level increased the expression of pro-apoptotic factors - Bax and TNF-α, intercellular protein - α-synuclein and reduced the expression of transcription factor - CREB. These neurofunctional variations are the key contributors to motor and cognitive abnormalities associated with PD. Nestin and GFAP expression study confirmed that 5-HT and GABA induced the differentiation and proliferation of the BMC to neurons and glial cells in the SNpc of rats. We also observed that activated astrocytes are playing a crucial role in the proliferation of transplanted BMC which makes them significant for stem cell-based therapy. Our molecular and behavioural results showed that 5-HT and GABA along with BMC potentiates a restorative effect by reversing the alterations in glutamate receptor binding, gene expression and behaviour abnormality that occur during PD. The therapeutic significance in Parkinson’s disease is of prominence.

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.

Pathological Investigations in penaeid Prawns

The thesis embodies the results of the studies carried out on certain diseases affecting the commercially important penaeid prawns in the capture and culture fisheries of the southwest and southeast coasts of india during october, 1981 to april 1985.initially a survey is conducted to obtain information and to understand the commom diseases and abnormalities occurring in the penaeid prawms in nature and those farmed. A result of the survey then cases of diseases and abnormalities are reported. These include tumour like growth soft prawm syndrome, tail necrosis brown spot disease, red rostrum, ciliate infestation ,helminth parasitisation,metacercarial infestation and bopyrid infestation in the penaeid prawns such as penaeus indicus p. monodon , p. semisulcatus ,Metapenaeus dobsoni and m.affinis.The symptoms ,occurrence and incidence of each of the above cases are provided along with the information on environmental factors such as salinity,dissolved oxygen,temperature and ph of the water from the collection sites. The nature of the disease,the tissuse of the host that are affected by the infection or infestation or by the pathogen ,and the actors influencing the infection in each of the ten cases are studied histopathologically and discussed. In the light of the available published information, the control measures for the different diseases of penaeid prawns are presented and discussed.

Studies on the pathobiology of penaeid larvae and postlarvae

The thesis presents the results of the studies carried out on certain diseases encountered in the larvae and postlarvae of penaeid prawns raised in the hatcheries at Cochin, Madras and Mandapam Camp during September 1985- April 1988. In the preliminary survey carried out to understand the common diseases occurring in the penaeid larvae and postlarvae, seven cases of diseases and abnormalities were encountered. These included ciliate infestation, Nit_zschia closteriurn infestation, parasitic protozoaninfection, parasitic dinoflagellate infection, appendage necrosis, heteromorphic eye and abnormal eggs and deformed nauplii .The clinical signs, seasonal occurrence and incidence of each of the above cases were provided along with the information on environmental factors such as salinity, dissolved oxygen, temperature and pH of the rearing medium. The Thésis is presented in nine chapters. Chapter 1 surveys the literature on the diseases of penaeid larvae, postlarvae and adult prawns from India and abroad. This is followed by a chapter on the material and methods employed during the present investigation. In the third chapter, seven cases of diseases and abnormalities encountered in the larvae and postlarvae of Penaeus indicus and p. semisulcatus during the survey carried out in the hatcheries located at different centres of Central‘ Marine Fisheries Research Institute are presented and discussed .A bacterium responsible for appendage necrosis was isolated and its taxonomy was studied. It was Gram-negative, fermentative and motile rod. It was sensitive to vibriostatic compound, 0/129. This bacterium was found to be a new isolate of vibrio on the basis of its morphological, biological, physiological and biochemical characters and comparison of these characters with those described for other related vibrios. This new isolate of vibrio was deposited in vibro Referrence Laboratory, Centres for Disease Control, Georgia, U.S.A. and coded as vibrio sp. 2448-88.

Investigations on pathologies in higher spin field theories

The present thesis deals with the studies on certain aspects of pathological higher field theories .It brings to light some new abnormalities and new samples of abnormal theories and also puts forward a novel approach towards the construction of trouble free theories

“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.

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.

Spectral clustering independent component analysis for tissue classification from brain MRI

A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases

Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

Wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions

Characterization and Pathogenicity of Vibrio cholerae and Vibrio vulnificus from Marine environments

The genus Vibrioof the family Vibrionaceae are Gram negative, oxidasepositive, rod- or curved- rodshaped facultative anaerobes, widespread in marine and estuarine environments. Vibrio species are opportunistic human pathogens responsible for diarrhoeal disease, gastroenteritis, septicaemia and wound infections and are also pathogens of aquatic organisms, causing infections to crustaceans, bivalves and fishes. In the present study, marine environmental samples like seafood and water and sediment samples from aquafarms and mangroves were screened for the presence of Vibrio species. Of the134 isolates obtained from the various samples, 45 were segregated to the genus Vibrio on the basis of phenotypic characterization.like Gram staining, oxidase test, MoF test and salinity tolerance. Partial 16S rDNA sequence analysis was utilized for species level identification of the isolates and the strains were identified as V. cholerae(N=21), V. vulnificus(N=18), V. parahaemolyticus(N=3), V. alginolyticus (N=2) and V. azureus (N=1). The genetic relatedness and variations among the 45 Vibrio isolates were elucidated based on 16S rDNA sequences. Phenotypic characterization of the isolates was based on their response to 12 biochemical tests namely Voges-Proskauers’s (VP test), arginine dihydrolase , tolerance to 3% NaCl test, ONPG test that detects β-galactosidase activity, and tests for utilization of citrate, ornithine, mannitol, arabinose, sucrose, glucose, salicin and cellobiose. The isolates exhibited diverse biochemical patterns, some specific for the species and others indicative of their environmental source.Antibiogram for the isolates was determined subsequent to testing their susceptibility to 12 antibiotics by the disc diffusion method. Varying degrees of resistance to gentamycin (2.22%), ampicillin(62.22%), nalidixic acid (4.44%), vancomycin (86.66), cefixime (17.77%), rifampicin (20%), tetracycline (42.22%) and chloramphenicol (2.22%) was exhibited. All the isolates were susceptible to streptomycin, co-trimoxazole, trimethoprim and azithromycin. Isolates from all the three marine environments exhibited multiple antibiotic resistance, with high MAR index value. The molecular typing methods such as ERIC PCR and BOX PCR revealed intraspecies relatedness and genetic heterogeneity within the environmental isolatesof V. cholerae and V. vulnificus. The 21 strains of V. choleraewere serogroupedas non O1/ non O139 by screening for the presence O1rfb and O139 rfb marker genes by PCR. The virulence/virulence associated genes namely ctxA, ctxB, ace, VPI, hlyA, ompU, rtxA, toxR, zot, nagst, tcpA, nin and nanwere screened in V. cholerae and V. vulnificusstrains.The V. vulnificusstrains were also screened for three species specific genes viz., cps, vvhand viu. In V. cholerae strains, the virulence associated genes like VPI, hlyA, rtxA, ompU and toxR were confirmed by PCR. All the isolates, except for strain BTOS6, harbored at least one or a combination of the tested genes and V. choleraestrain BTPR5 isolated from prawn hosted the highest number of virulence associated genes. Among the V. vulnificusstrains, only 3 virulence genes, VPI, toxR and cps, were confirmed out of the 16 tested and only 7 of the isolates had these genes in one or more combinations. Strain BTPS6 from aquafarm and strain BTVE4 from mangrove samples yielded positive amplification for the three genes. The toxRgene from 9 strains of V. choleraeand 3 strains of V. vulnificus were cloned and sequenced for phylogenetic analysis based on nucleotide and the amino acid sequences. Multiple sequence alignment of the nucleotide sequences and amino acid sequences of the environmental strains of V. choleraerevealed that the toxRgene in the environmental strains are 100% homologous to themselves and to the V. choleraetoxR gene sequence available in the Genbank database. The 3 strains of V. vulnificus displayed high nucleotide and amino acid sequence similarity among themselves and to the sequences of V. cholerae and V. harveyi obtained from the GenBank database, but exhibited only 72% homology to the sequences of its close relative V. vulnificus. Structure prediction of the ToxR protein of Vibrio cholerae strain BTMA5 was by PHYRE2 software. The deduced amino acid sequence showed maximum resemblance with the structure of DNA-binding domain of response regulator2 from Escherichia coli k-12 Template based homology modelling in PHYRE2 successfully modelled the predicted protein and its secondary structure based on protein data bank (PDB) template c3zq7A. The pathogenicity studies were performed using the nematode Caenorhabditiselegansas a model system. The assessment of pathogenicity of environmental strain of V. choleraewas conducted with E. coli strain OP50 as the food source in control plates, environmental V. cholerae strain BTOS6, negative for all tested virulence genes, to check for the suitability of Vibrio sp. as a food source for the nematode;V. cholerae Co 366 ElTor, a clinical pathogenic strain and V. cholerae strain BTPR5 from seafood (Prawn) and positive for the tested virulence genes like VPI, hlyA, ompU,rtxA and toxR. It was found that V. cholerae strain BTOS6 could serve as a food source in place of E. coli strain OP50 but behavioral aberrations like sluggish movement and lawn avoidance and morphological abnormalities like pharyngeal and intestinal distensions and bagging were exhibited by the worms fed on V. cholerae Co 366 ElTor strain and environmental BTPR5 indicating their pathogenicity to the nematode. Assessment of pathogenicity of the environmental strains of V. vulnificus was performed with V. vulnificus strain BTPS6 which tested positive for 3 virulence genes, namely, cps, toxRand VPI, and V. vulnificus strain BTMM7 that did not possess any of the tested virulence genes. A reduction was observed in the life span of worms fed on environmental strain of V. vulnificusBTMM7 rather than on the ordinary laboratory food source, E. coli OP50. Behavioral abnormalities like sluggish movement, lawn avoidance and bagging were also observed in the worms fed with strain BTPS6, but the pharynx and the intestine were intact. The presence of multi drug resistant environmental Vibrio strainsthat constitute a major reservoir of diverse virulence genes are to be dealt with caution as they play a decisive role in pathogenicity and horizontal gene transfer in the marine environments.

Trajectory and Force Control of a Direct Drive Arm

Using the MIT Serial Link Direct Drive Arm as the main experimental device, various issues in trajectory and force control of manipulators were studied in this thesis. Since accurate modeling is important for any controller, issues of estimating the dynamic model of a manipulator and its load were addressed first. Practical and effective algorithms were developed fro the Newton-Euler equations to estimate the inertial parameters of manipulator rigid-body loads and links. Load estimation was implemented both on PUMA 600 robot and on the MIT Serial Link Direct Drive Arm. With the link estimation algorithm, the inertial parameters of the direct drive arm were obtained. For both load and link estimation results, the estimated parameters are good models of the actual system for control purposes since torques and forces can be predicted accurately from these estimated parameters. The estimated model of the direct drive arm was them used to evaluate trajectory following performance by feedforward and computed torque control algorithms. The experimental evaluations showed that the dynamic compensation can greatly improve trajectory following accuracy. Various stability issues of force control were studied next. It was determined that there are two types of instability in force control. Dynamic instability, present in all of the previous force control algorithms discussed in this thesis, is caused by the interaction of a manipulator with a stiff environment. Kinematics instability is present only in the hybrid control algorithm of Raibert and Craig, and is caused by the interaction of the inertia matrix with the Jacobian inverse coordinate transformation in the feedback path. Several methods were suggested and demonstrated experimentally to solve these stability problems. The result of the stability analyses were then incorporated in implementing a stable force/position controller on the direct drive arm by the modified resolved acceleration method using both joint torque and wrist force sensor feedbacks.

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques