Three-dimensional anatomical model-based segmentation of MR brainimages through principal axes registration

Model-based segmentation and analysis of brain images depends on anatomical knowledge which may be derived from conventional atlases. Classical anatomical atlases are based on the rigid spatial distribution provided by a single cadaver. Their use to segment internal anatomical brain structures in a high-resolution MR brain image does not provide any knowledge about the subject variability, and therefore they are not very efficient in analysis. The authors present a method to develop three-dimensional computerized composite models of brain structures to build a computerized anatomical atlas. The composite models are developed using the real MR brain images of human subjects which are registered through the principal axes transformation. The composite models provide probabilistic spatial distributions, which represent the variability of brain structures and can be easily updated for additional subjects. The authors demonstrate the use of such a composite model of ventricular structure to help segmentation of the ventricles and cerebrospinal fluid of MR brain images. Here, a composite model of ventricles using a set of 22 human subjects is developed and used in a model-based segmentation of ventricles, sulci, and white matter lesions. To illustrate the clinical usefulness, automatic volumetric measurements on ventricular size and cortical atrophy for an additional eight alcoholics and 10 normal subjects were made. The volumetric quantitative results indicated regional brain atrophy in chronic alcoholics     

Thin conducting polypyrrole film on insulating surface and its applications

An electrically conductive plastic material was obtained by the polymerization of pyrrole on insulating polymeric materials and nylon cloth impregnated with the oxidant by vapour phase technique, resulting in a uniform, smooth and adherent coating of conducting polymer having a surface resistance ranging from 200 Ω/□ to 20 kΩ/□, which makes it suitable for applications as an antistatic material.     

The metabolic anatomy of tremor in Parkinson's disease

OBJECTIVE: To identify regional metabolic brain networks related specifically to the presence of tremor in PD. BACKGROUND: The pathophysiology of parkinsonian tremor is unknown. Because tremor in PD occurs mainly in repose, we used resting state PET with 18F-fluorodeoxyglucose (FDG) to identify specific metabolic brain networks associated with this clinical manifestation. METHODS: We studied two discrete groups of eight PD patients with and without tremor using FDG/PET. Both patient groups were matched for gender, age, and Unified Parkinson Disease Rating Scale ratings for akinesia and rigidity. Ten normal volunteer subjects served as controls. RESULTS: Network analysis with the Scaled Subprofile Model was performed in two steps. 1) We computed the expression of the PD-related pattern (PDRP) identified by us previously in each of the PD patients and control subjects. Although PDRP subject scores were abnormally elevated in the combined PD cohort (p < 0.005), these values did not differ in the PD patient groups with and without tremor (p = 0.36). 2) We used SSM to analyze the data from the combined PD cohort comprising both patient groups. We found that PD patients with tremor were characterized by increased expression of a metabolic network comprising the thalamus, pons, and premotor cortical regions. Subject scores for this pattern were elevated in the tremor group compared with the atremulous patient group and the normal control group (p < 0.005). CONCLUSIONS: The findings suggest that PD patients with tremor are characterized by distinct increases in the functional activity of thalamo-motor cortical projections. Modulation of this functional anatomic pathway is likely to be the mechanism for successful interventions for the relief of parkinsonian tremor.     

Analysis of mammographic microcalcifications using gray-level image structure features

At present, mammography associated with clinical breast examination and breast self-examination is the only effective and viable method for mass breast screening. The presence of microcalcifications is one of the primary signs of breast cancer. It is, difficult however, to distinguish between benign and malignant microcalcifications associated with breast cancer. Here, the authors define a set of image structure features for classification of malignancy. Two categories of correlated gray-level image structure features are defined for classification of "difficult-to-diagnose" cases. The first category of features includes second-order histogram statistics-based features representing the global texture and the wavelet decomposition-based features representing the local texture of the microcalcification area of interest. The second category of features represents the first-order gray-level histogram-based statistics of the segmented microcalcification regions and the size, number, and distance features of the segmented microcalcification cluster. Various features in each category were correlated with the biopsy examination results of 191 "difficult-to-diagnose" cases for selection of the best set of features representing the complete gray-level image structure information. The selection of the best features was performed using the multivariate cluster analysis as well as a genetic algorithm (GA)-based search method. The selected features were used for classification using backpropagation neural network and parameteric statistical classifiers. Receiver operating characteristic (ROC) analysis was performed to compare the neural network-based classification with linear and k-nearest neighbor (KNN) classifiers. The neural network classifier yielded better results using the combined set of features selected through the GA-based search method for classification of "difficult-to-diagnose" microcalcifications.     

Nevoscopy: three-dimensional computed tomography of nevi and melanomas in situ by transillumination

The thickness of a malignant nevus has been found to be an important prognostic factor for patients with melanoma. We have designed a new method of imaging nevi that permits their thickness to be measured in situ. Using fiber optics directed into the surrounding skin, we transilluminate the nevus. Three images are picked up by a digitizing TV camera: the vertical image (90 degrees ), a glancing image (180 degrees ), and one at 45 degrees , obtained by using two front-silvered mirrors held next to the nevus in a "nevoscope." The digitized images are used in a computed tomography algorithm to calculate approximate vertical cross sections of the nevus. The algorithm is one we recently developed to permit reconstruction from a very few projections. Our method is completely noninvasive. It may be used to check all the nevi on a patient. Without excisions, we could establish a baseline three-dimensional shape for each nevus, follow any changes in time, and obtain an early warning of increase in thickness and possible malignancy.     

Minimising total cost with regular and emergency outsourcing sources: a neuro-dynamic programming approach

This study models and explains the business situation of an organisation which has regular and emergency outsourcing sources and where decisions have to be made at the beginning of every period regarding how much to order from these sources, so as to balance between different cost components of current and future periods. Previous works in this area have tried to attack this problem with dynamic programming. In this project, neuro-dynamic programming has been applied, and the reasons for doing so have been clearly stated. This model not only derives policies in order to minimise the expected total discounted cost over a period of time, but also enables the system to learn to make such decisions, and to improve its actions by using reinforcement learning. The performance of the present work has been measured quantitatively and has been compared with the models stated in literature. This study will be very useful for the organisations where such business problems exist or are likely to exist. This study will also be of great use to researchers, who are keen to understand and model the given business situation with distribution independent demand based models.     

Classification of melanoma using tree structured wavelet transforms

This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus. The results are also compared with those obtained using another method of developing tree structures utilizing the maximum channel energy criteria with a fixed energy ratio threshold.     

Three dimensional reconstruction of coronary arteries from two views

Geometric representation and measurements of localized lumen stenosis of coronary arteries are important considerations in the diagnosis of cardiovascular diseases. This discrete narrowing of the arteries typically impairs blood flow in regions of the heart, and can be present along the entire length of the artery. Three-dimensional (3-D) reconstruction of coronary arterial tree allows clinician to visualize vascular geometry. Three-dimensional representation of tree topology facilitates calculation of hemodynamic measurements to study myocardial infarction and stenosis. The 3-D arterial tree, computed from two views, can provide more information about the tree geometry than individual views. In this paper, a 3-step algorithm for 3-D reconstruction of arterial tree using two standard views is presented. The first step is a multi-resolution segmentation of the coronary vessels followed by medial-axis detection along the entire arterial tree for both views. In the second step, arterial trees from the two views are registered using medial-axis representation at the coarsest resolution level to obtain an initial 3-D reconstruction. This initial reconstruction at the coarsest level is then modified using 3-D geometrical a priori information. In the third step, the modified reconstruction is projected on the next higher-resolution segmented medial-axis representation and an updated reconstruction is obtained at the higher resolution. The process is iterated until the final 3-D reconstruction is obtained at the finest resolution level. Linear programming based constrained optimization method is used for registering two views at the coarse resolution. This is followed by a Tree-Search method for registering detailed branches at higher resolutions. The automated 3-D reconstruction method was evaluated on computer-simulated as well as human angiogram data. Results show that the automated 3-D reconstruction method provided good registration of computer-simulated data. On human angiogram data, the computed 3-D reconstruction matched well with manual registration.     

Study of air oxidation of amorphous Zr<Subscript>65</Subscript>Cu<Subscript>17.5</Subscript>Ni<Subscript>10</Subscript>Al<Subscript>7.5</Subscript> by X-ray photoelectron spectroscopy (XPS)

The oxidation of the bulk amorphous alloy Zr₆₅Cu_17.5Ni₁₀Al_7.5 in air in its amorphous and the supercooled liquid states was studied in the temperature range 573–663 K using X-ray photoelectron spectroscopy (XPS). The oxide film mainly consisted of the oxides of Zr (as ZrO₂) and Al (as Al₂O₃). No Cu or Ni was found in the oxide film formed on the amorphous state of the alloy while significant Cu (as CuO) was present in the oxide film formed on the alloy in its supercooled liquid state. The role of the various alloying elements during oxidation at high temperatures in air is discussed in the paper. The XPS data from oxide film support the previously suggested mechanism for oxidation of this alloy, i.e. the rate controlling process during oxidation of the alloy at low temperatures (in the amorphous state) is the back-diffusion of Ni and Cu, while the oxidation at high temperatures (in the supercooled liquid state) is dominated by the inward diffusion of oxygen.