SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.

Measurement Function Design for Visual Tracking Applications

Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.

Compact tiled display with uniform illumination

The demand for more pixels is beginning to be met as manufacturers increase the native resolution of projector chips. Tiling several projectors still offers a solution to augment the pixel capacity of a display. However, problems of color and illumination uniformity across projectors need to be addressed as well as the computer software required to drive such devices. We present the results obtained on a desktop-size tiled projector array of three D-ILA projectors sharing a common illumination source. A short throw lens (0.8:1) on each projector yields a 21-in. diagonal for each image tile; the composite image on a 3×1 array is 3840×1024 pixels with a resolution of about 80 dpi. The system preserves desktop resolution, is compact, and can fit in a normal room or laboratory. The projectors are mounted on precision six-axis positioners, which allow pixel level alignment. A fiber optic beamsplitting system and a single set of red, green, and blue dichroic filters are the key to color and illumination uniformity. The D-ILA chips inside each projector can be adjusted separately to set or change characteristics such as contrast, brightness, or gamma curves. The projectors were then matched carefully: photometric variations were corrected, leading to a seamless image. Photometric measurements were performed to characterize the display and are reported here. This system is driven by a small PC cluster fitted with graphics cards and running Linux. It can be scaled to accommodate an array of 2×3 or 3×3 projectors, thus increasing the number of pixels of the final image. Finally, we present current uses of the display in fields such as astrophysics and archaeology (remote sensing).

Scalable Visualization of Galaxies, Oceans, and Brains

One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

Simultaneous X-ray imaging of plant root growth and water uptake in thin-slab systems

Direct and simultaneous observation of root growth and plant water uptake is difficult because soils are opaque. X-ray imaging techniques such as projection radiography or Computer Tomography (CT) offer a partial alternative to such limitations. Nevertheless, there is a trade-off between resolution, large field-of-view and 3-dimensionality: With the current state of the technology, it is possible to have any two. In this study, we used X-ray transmission through thin-slab systems to monitor transient saturation fields that develop around roots as plants grow. Although restricted to 2-dimensions, this approach offers a large field-of-view together with high spatial and dynamic resolutions. To illustrate the potential of this technology, we grew peas in 1 cm thick containers filled with soil and imaged them at regular intervals. The dynamics of both the root growth and the water content field that developed around the roots could be conveniently monitored. Compared to other techniques such as X-ray CT, our system is relatively inexpensive and easy to implement. It can potentially be applied to study many agronomic problems, such as issues related to the impact of soil constraints (physical, chemical or biological) on root development.

Improved detection of incipient vascular changes by a biotechnological platform combining post mortem MRI in situ with neuropathology

The histopathological counterpart of white matter hyperintensities is a matter of debate. Methodological and ethical limitations have prevented this question to be elucidated. We want to introduce a protocol applying state-of-the-art methods in order to solve fundamental questions regarding the neuroimaging-neuropathological uncertainties comprising the most common white matter hyperintensities [WMHs] seen in aging. By this protocol, the correlation between signal features in in situ, post mortem MRI-derived methods, including DTI and MTR and quantitative and qualitative histopathology can be investigated. We are mainly interested in determining the precise neuroanatomical substrate of incipient WMHs. A major issue in this protocol is the exact co-registration of small lesion in a tridimensional coordinate system that compensates tissue deformations after histological processing. The protocol is based on four principles: post mortem MRI in situ performed in a short post mortem interval, minimal brain deformation during processing, thick serial histological sections and computer-assisted 3D reconstruction of the histological sections. This protocol will greatly facilitate a systematic study of the location, pathogenesis, clinical impact, prognosis and prevention of WMHs. (C) 2009 Elsevier B.V. All rights reserved.

Long-Term Astroglial Reaction and Neuronal Plasticity in the Subcortical Visual Pathways After a Complete Ablation of Telencephalon in Pigeons (Columba livia)

This paper analyzes the astroglial and neuronal responses in subtelencephalic structures, following a bilateral ablation of the telencephalon in the Columba livia pigeons. Control birds received a sham operation. Four months later the birds were sacrificed and their brains processed for glial fribillary acid protein (GFAP) and neurofilament immunohistochemistry, markers for astrocytes and neurons, respectively. Computer-assisted image analysis was employed for quantification of the immunoreactive labeling in the nucleus rotundus (N.Rt) and the optic tectum (OT) of the birds. An increased number of GFAP immunoreactive astrocytes were found in several subregions of the N.Rt (p .001), as well as in layers 1, 2cd, 3, and 6 of the OT (p .001) of the lesioned animals. Neurofilament immunoreactivity decreased massively in the entire N.Rt of the lesioned birds; however, remaining neurons with healthy aspect showing large cytoplasm and ramified branches were detected mainly in the periphery of the nucleus. In view of the recently described paracrine neurotrophic properties of the activated astrocytes, the data of the present study may suggest a long-lasting neuroglial interaction in regions of the lesioned bird brain far from injury. Such events may trigger neuronal plasticity in remaining brain structures that may lead spontaneous behavior recovery as the one promoted here even after a massive injury.

Theory and applications of fuzzy Volterra integral equations

Formulations of fuzzy integral equations in terms of the Aumann integral do not reflect the behavior of corresponding crisp models. Consequently, they are ill-adapted to describe physical phenomena, even when vagueness and uncertainty are present. A similar situation for fuzzy ODEs has been obviated by interpretation in terms of families of differential inclusions. The paper extends this formalism to fuzzy integral equations and shows that the resulting solution sets and attainability sets are fuzzy and far better descriptions of uncertain models involving integral equations. The investigation is restricted to Volterra type equations with mildly restrictive conditions, but the methods are capable of extensive generalization to other types and more general assumptions. The results are illustrated by integral equations relating to control models with fuzzy uncertainties.

Three-dimensional space-borne synthetic aperture radar (SAR) imaging with multiple pass processing

Three-dimensional (3D) synthetic aperture radar (SAR) imaging via multiple-pass processing is an extension of interferometric SAR imaging. It exploits more than two flight passes to achieve a desired resolution in elevation. In this paper, a novel approach is developed to reconstruct a 3D space-borne SAR image with multiple-pass processing. It involves image registration, phase correction and elevational imaging. An image model matching is developed for multiple image registration, an eigenvector method is proposed for the phase correction and the elevational imaging is conducted using a Fourier transform or a super-resolution method for enhancement of elevational resolution. 3D SAR images are obtained by processing simulated data and real data from the first European Remote Sensing satellite (ERS-1) with the proposed approaches.

Cationic drug pharmacokinetics in diseased livers determined by fibrosis index, hepatic protein content, microsomal activity, and nature of drug

The disposition kinetics of six cationic drugs in perfused diseased and normal rat livers were determined by multiple indicator dilution and related to the drug physicochemical properties and liver histopathology. A carbon tetrachloride (CCl4)induced acute hepatocellular injury model had a higher fibrosis index (FI), determined by computer-assisted image analysis, than did an alcohol-induced chronic hepatocellular injury model. The alcohol-treated group had the highest hepatic alpha(1)- acid glycoprotein, microsomal protein (MP), and cytochrome P450 (P450) concentrations. Various pharmacokinetic parameters could be related to the octanol-water partition coefficient (log P-app) of the drug as a surrogate for plasma membrane partition coefficient and affinity for MP or P450, the dependence being lower in the CCl4-treated group and higher in the alcohol-treated group relative to controls. Stepwise regression analysis showed that hepatic extraction ratio, permeability-surface area product, tissue-binding constant, intrinsic clearance, partition ratio of influx (k(in)) and efflux rate constant (k(out)), and k(in)/k(out) were related to physicochemical properties of drug (log P-app or pK(a)) and liver histopathology (FI, MP, or P450). In addition, hepatocyte organelle ion trapping of cationic drugs was evident in all groups. It is concluded that fibrosis-inducing hepatic disease effects on cationic drug disposition in the liver may be predicted from drug properties and liver histopathology.

Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces

Combinatorial optimization problems share an interesting property with spin glass systems in that their state spaces can exhibit ultrametric structure. We use sampling methods to analyse the error surfaces of feedforward multi-layer perceptron neural networks learning encoder problems. The third order statistics of these points of attraction are examined and found to be arranged in a highly ultrametric way. This is a unique result for a finite, continuous parameter space. The implications of this result are discussed.