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.

Sequential extraction and single-step cold-acid extraction: A feasibility study for use with freshwater-canal sediments

This investigation examines metal release from freshwater sediment using sequential extraction and single-step cold-acid leaching. The concentrations of Cd, Cr, Cu, Fe, Ni, Pb and Zn released using a standard 3-step sequential extraction (Rauret et al., 1999) are compared to those released using a 0.5 M HCl; leach. The results show that the three sediments behave in very different ways when subject to the same leaching experiments: the cold-acid extraction appears to remove higher relative concentrations of metals from the iron-rich sediment than from the other two sediments. Cold-acid extraction appears to be more effective at removing metals from sediments with crystalline iron oxides than the "reducible" step of the sequential extraction. The results show that a single-step acid leach can be just as effective as sequential extractions at removing metals from sediment and are a great deal less time-consuming.

Solvent extraction and lanthanide complexation studies with new terdentate ligands containing two 1,3,5-triazine moieties

The extracting agent 2,6-bis(4,6-di-pivaloylamino-1,3,5-triazin-2-yl)-pyridine (L-5) in n-octanol was found, in synergy with 2-bromodecanoic acid, to give D-Am/D-Eu separation factors (SFs) between 2.4 and 3.7 when used to extract the metal ions from 0.02-0.12 M HNO3. Slightly higher SFs (4-6) were obtained in the absence of the synergist when the ligand was used to extract Am(III) and Eu(III) from 0.98 M HNO3. In order to investigate the possible nature of the extracted species crystal structures of L-5 and the complex formed between Yb(III) with 2,6-bis(4,6-di-amino-1,3,5-triazin-2-yl)-pyridine (L-4) were also determined. The structure of L-5 shows 3 methanol solvent molecules all of which form 2 or 3 hydrogen bonds with triazine nitrogen atoms, amide nitrogen or oxygen atoms, or pyridine nitrogen atoms. However, L-5 is relatively unstable in metal complexation reactions and loses amide groups to form the parent tetramine L-4. The crystal structure of Yb(L-4)(NO3)(3) shows ytterbium in a 9-coordinate environment being bonded to three donor atoms of the ligand and three bidentate nitrate ions. The solvent extraction properties of L-4 and L-5 are far inferior to those found for the 2,6-bis-(1,2,4-triazin-3-yl)-pyridines (L-1) which have SF values of ca. 140 and theoretical calculations have been made to compare the electronic properties of the ligands. The electronic charge distribution in L-4 and L-5 is similar to that found in other terdentate ligands such as terpyridine which have equally poor extraction properties and suggests that the unique properties of L-1 evolve from the presence of two adjacent nitrogen atoms in the triazine rings.

Extraction and coordination studies of the unexplored bifunctional ligand carbamoyl methyl sulfoxide (CMSO) with uranium(VI) and cerium(III) nitrates. Synthesis and structures of [UO2(NO3)(2)((PhSOCH2CONBu2)-Bu-i)] and [Ce(NO3)(3)(PhSOCH2CONBu2)(2)]

The bifunctional carbamoyl methyl sulfoxide ligands, PhCH2SOCH2CONHPh (L-1), PhCH2SOCH2CONHCH2Ph (L-2), (PhSOCH2CONPr2)-Pr-i (L-3), PhSOCH2CONBu2 (L-4), (PhSOCH2CONBu2)-Bu-i (L-5) and PhSOCH2CON(C8H17)(2) (L-6) have been synthesized and characterized by spectroscopic methods. The selected coordination chemistry of L-1, L-3, L-4 and L-5 with [UO2(NO3)(2)] and [Ce(NO3)(3)] has been evaluated. The structures of the compounds [UO2(NO3)(2)((PhSOCH2CONBu2)-Bu-i)] (10) and [Ce(NO3)(3)(PhSOCH2CONBu2)(2)] (12) have been determined by single crystal X-ray diffraction methods. Preliminary extraction studies of ligand L-6 with U(VI), Pu(IV) and Am(III) in tracer level showed an appreciable extraction for U(VI) and Pu(IV) in up to 10 M HNO3 but not for Am(III). Thermal studies on compounds 8 and 10 in air revealed that the ligands can be destroyed completely on incineration. The electron spray mass spectra of compounds 8 and 10 in acetone show that extensive ligand distribution reactions occur in solution to give a mixture of products with ligand to metal ratios of 1 : 1 and 2 : 1. However, 10 retains its solid state structure in CH2Cl2.

Extraction and determination of ellagic acid content in chestnut bark and fruit

Chestnuts are an important economic resource in the chestnut growing regions, not only for the fruit, but also for the wood. The content of ellagic acid (EA), a naturally occurring inhibitor of carcinogenesis, was determined in chestnut fruits and bark. EA was extracted with methanol and free ellagic acid was determined by HPLC with UV detection, both in the crude extract and after hydrolysis. The concentration of EA was generally increased after hydrolysis due to the presence of ellagitannins in the crude extract. The concentration varied between 0.71 and 21.6 ing g(-1) (d.w.) in un-hydrolyzed samples, and between 2.83 and 18.4 mg g(-1) (d.w.) ill hydrolyzed samples. In chestnut fruits, traces of EA were present in the seed, with higher concentrations in the pellicle and pericarp. However, all fruit tissues had lower concentrations of EA than had the bark. The concentration of EA in the hydrolyzed samples showed a non-linear correlation with the concentration in the unhydrolyzed extracts. (C) 2008 Elsevier Ltd. All rights reserved.

Facial feature extraction and selection by Gabor wavelets and boosting

In this paper, we present a feature selection approach based on Gabor wavelet feature and boosting for face verification. By convolution with a group of Gabor wavelets, the original images are transformed into vectors of Gabor wavelet features. Then for individual person, a small set of significant features are selected by the boosting algorithm from a large set of Gabor wavelet features. The experiment results have shown that the approach successfully selects meaningful and explainable features for face verification. The experiments also suggest that for the common characteristics such as eyes, noses, mouths may not be as important as some unique characteristic when training set is small. When training set is large, the unique characteristics and the common characteristics are both important.

A neurofuzzy network knowledge extraction and extended gram-Schmidt algorithm for model subspace decomposition

This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality

A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Video activity extraction and reporting with incremental unsupervised learning

The present work presents a new method for activity extraction and reporting from video based on the aggregation of fuzzy relations. Trajectory clustering is first employed mainly to discover the points of entry and exit of mobiles appearing in the scene. In a second step, proximity relations between resulting clusters of detected mobiles and contextual elements from the scene are modeled employing fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows building the structure of the scene and characterises the ongoing different activities of the scene. Discovered activity zones can be reported as activity maps with different granularities thanks to the analysis of the transitive closure matrix. Taking advantage of the soft relation properties, activity zones and related activities can be labeled in a more human-like language. We present results obtained on real videos corresponding to apron monitoring in the Toulouse airport in France.

Perturbation, extraction and refinement of invariant pairs for matrix polynomials

Generalizing the notion of an eigenvector, invariant subspaces are frequently used in the context of linear eigenvalue problems, leading to conceptually elegant and numerically stable formulations in applications that require the computation of several eigenvalues and/or eigenvectors. Similar benefits can be expected for polynomial eigenvalue problems, for which the concept of an invariant subspace needs to be replaced by the concept of an invariant pair. Little has been known so far about numerical aspects of such invariant pairs. The aim of this paper is to fill this gap. The behavior of invariant pairs under perturbations of the matrix polynomial is studied and a first-order perturbation expansion is given. From a computational point of view, we investigate how to best extract invariant pairs from a linearization of the matrix polynomial. Moreover, we describe efficient refinement procedures directly based on the polynomial formulation. Numerical experiments with matrix polynomials from a number of applications demonstrate the effectiveness of our extraction and refinement procedures.

Optimisation of the extraction and processing conditions of chamomile (Matricaria chamomilla L.) for incorporation into a beverage

The total phenols, apigenin 7-glucoside, turbidity and colour of extracts from dried chamomile flowers were studied with a view to develop chamomile extracts with potential anti-inflammatory properties for incorporation into beverages. The extraction of all constituents followed pseudo first-order kinetics. In general, the rate constant (k) increased as the temperature increased from 57 to 100 °C. The turbidity only increased significantly between 90 and 100 °C. Therefore, aqueous chamomile extracts had maximum total phenol concentration and minimum turbidity when extracted at 90 °C for 20 min. The effect of drying conditions on chamomile extracted using these conditions was determined. A significant reduction in phenol concentration, from 19.7 ± 0.5 mg/g GAE in fresh chamomile to 13 ± 1 mg/g GAE, was found only in the plant material oven-dried at 80 °C (p ⩽ 0.05). The biggest colour change was between fresh chamomile and that oven-dried at 80 °C, followed by samples air-dried. There was no significant difference in colour of material freeze-dried and oven-dried at 40 °C.

Towards pain-free diagnosis of skin diseases through multiplexed microneedles: biomarker extraction and detection using a highly sensitive blotting method

Immunodiagnostic microneedles provide a novel way to extract protein biomarkers from the skin in a minimally invasive manner for analysis in vitro. The technology could overcome challenges in biomarker analysis specifically in solid tissue, which currently often involves invasive biopsies. This study describes the development of a multiplex immunodiagnostic device incorporating mechanisms to detect multiple antigens simultaneously, as well as internal assay controls for result validation. A novel detection method is also proposed. It enables signal detection specifically at microneedle tips and therefore may aid the construction of depth profiles of skin biomarkers. The detection method can be coupled with computerised densitometry for signal quantitation. The antigen specificity, sensitivity and functional stability of the device were assessed against a number of model biomarkers. Detection and analysis of endogenous antigens (interleukins 1α and 6) from the skin using the device was demonstrated. The results were verified using conventional enzyme-linked immunosorbent assays. The detection limit of the microneedle device, at ≤10 pg/mL, was at least comparable to conventional plate-based solid-phase enzyme immunoassays.

Antioxidant therapy attenuates oxidative stress in the blood of subjects exposed to occupational airborne contamination from coal mining extraction and incineration of hospital residues

Coal mining and incineration of solid residues of health services (SRHS) generate several contaminants that are delivered into the environment, such as heavy metals and dioxins. These xenobiotics can lead to oxidative stress overgeneration in organisms and cause different kinds of pathologies, including cancer. In the present study the concentrations of heavy metals such as lead, copper, iron, manganese and zinc in the urine, as well as several enzymatic and non-enzymatic biomarkers of oxidative stress in the blood (contents of lipoperoxidation = TBARS, protein carbonyls = PC, protein thiols = PT, alpha-tocopherol = AT, reduced glutathione = GSH, and the activities of glutathione S-transferase = GST, glutathione reductase = GR, glutathione peroxidase = GPx, catalase = CAT and superoxide dismutase = SOD), in the blood of six different groups (n = 20 each) of subjects exposed to airborne contamination related to coal mining as well as incineration of solid residues of health services (SRHS) after vitamin E (800 mg/day) and vitamin C (500 mg/day) supplementation during 6 months, which were compared to the situation before the antioxidant intervention (Avila et al., Ecotoxicology 18:1150-1157, 2009; Possamai et al., Ecotoxicology 18:1158-1164, 2009). Except for the decreased manganese contents, heavy metal concentrations were elevated in all groups exposed to both sources of airborne contamination when compared to controls. TBARS and PC concentrations, which were elevated before the antioxidant intervention decreased after the antioxidant supplementation. Similarly, the contents of PC, AT and GSH, which were decreased before the antioxidant intervention, reached values near those found in controls, GPx activity was reestablished in underground miners, and SOD, CAT and GST activities were reestablished in all groups. The results showed that the oxidative stress condition detected previously to the antioxidant supplementation in both directly and indirectly subjects exposed to the airborne contamination from coal dusts and SRHS incineration, was attenuated after the antioxidant intervention.

Dynamic Solid Phase DNA Extraction and PCR Amplification in Polyester-Toner Based Microchip

A variety of substrates have been used for fabrication of microchips for DNA extraction, PCR amplification, and DNA fragment separation, including the more conventional glass and silicon as well as alternative polymer-based materials. Polyester represents one such polymer, and the laser-printing of toner onto polyester films has been shown to be effective for generating polyester-toner (PeT) microfluidic devices with channel depths on the order of tens of micrometers. Here, we describe a novel and simple process that allows for the production of multilayer, high aspect-ratio PeT microdevices with substantially larger channel depths. This innovative process utilizes a CO(2) laser to create the microchannel in polyester sheets containing a uniform layer of printed toner, and multilayer devices can easily be constructed by sandwiching the channel layer between uncoated cover sheets of polyester containing precut access holes. The process allows the fabrication of deep channels, with similar to 270 mu m, and we demonstrate the effectiveness of multilayer PeT microchips for dynamic solid phase extraction (dSPE) and PCR amplification. With the former, we found that (i) more than 65% of DNA from 0.6 mu L of blood was recovered, (ii) the resultant DNA was concentrated to greater than 3 ng/mu L., (which was better than other chip-based extraction methods), and (iii) the DNA recovered was compatible with downstream microchip-based PCR amplification. Illustrative of the compatibility of PeT microchips with the PCR process, the successful amplification of a 520 bp fragment of lambda-phage DNA in a conventional thermocycler is shown. The ability to handle the diverse chemistries associated with DNA purification and extraction is a testimony to the potential utility of PeT microchips beyond separations and presents a promising new disposable platform for genetic analysis that is low cost and easy to fabricate.

Polydimethylsiloxane/polypyrrole stir bar sorptive extraction and liquid chromatography (SBSE/LC-UV) analysis of antidepressants in plasma samples

A new polymeric coating consisting of a dual-phase, polydimethylsiloxane (PDMS) and polypyrrole (PPY) was developed for the stir bar sorptive extraction (SBSE) of antidepressants (mirtazapine, citalopram, paroxetine, duloxetine, fluoxetine and sertraline) from plasma samples, followed by liquid chromatography analysis (SBSE/LC-UV). The extractions were based on both adsorption (PPY) and sorption (PDMS) mechanisms. SBSE variables, such as extraction time, temperature, pH of the matrix, and desorption time were optimized, in order to achieve suitable analytical sensitivity in a short time period. The PDMS/PPY coated stir bar showed high extraction efficiency (sensitivity and selectivity) toward the target analytes. The quantification limits (LOQ) of the SBSE/LC-UV method ranged from 20 ng mL(-1) to 50 ng mL(-1), and the linear range was from LOQ to 500 ng mL(-1), with a determination coefficient higher than 0.99. The inter-day precision of the SBSE/LC-UV method presented a variation coefficient lower than 15%. The efficiency of the SBSE/LC-UV method was proved by analysis of plasma samples from elderly depressed patients. (C) 2008 Elsevier B.V. All rights reserved.