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As new concepts such as virtualization, cloud computing, and web applications continue to emerge, XML has begun to assume the role as the universal language for communication among contrasting systems that grow throughout the internet. Innovations in XML Applications and Metadata Management: Advancing Technologies addresses the functionality between XML and its related technologies towards application development based on previous concepts. This book aims to highlights the variety of purposes for XML applications and how the technology development brings together advancements in the virtual world.

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Some scenes and objects have a wide range of brightness that cannot be captured with a conventional camera. This limitation, which degrades the dynamic range of an imaged scene or object, is addressed by use of high dynamic range (HDR) imaging techniques. With HDR imaging techniques, images of a very broad range of intensity can be obtained with conventional cameras. Another limitation of conventional cameras is the range of wavelength that they can capture. Outside the visible wavelengths, the responsivity of conventional cameras drops; therefore, a conventional camera cannot capture images in nonvisible wavelengths. Compressive imaging is a solution for this problem. Compressive imaging reduces the number of pixels of a camera to one, so a camera can be replaced by a detector with one pixel. The range of wavelengths to which such detectors are responsive is much wider than that of a conventional camera. A combination of HDR imaging and compressive imaging is introduced and is benefitted from the advantages of both techniques. An algorithm that combines these two techniques is proposed, and results are presented. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.7.071407]

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Dermoscopy is a non-invasive diagnosis technique for in vivo observation of pigmented skin lesions used in dermatology. There is currently a great interest in the development of computer assisted diagnosis systems, given their great potential to this area of medicine. The standard approach in automatic dermoscopic image analysis can be divided in three stages: image segmentation, feature extraction/selection and lesion classification. In order to validate the algorithms developed for each stage, a great number of reliable images and clinical diagnosis are required. This paper presents a software tool to collect and organize dermoscopic data from hospital databases. It is suitable for clinical daily routine and simultaneously has a datastructure to support the development and validation of algorithms created by the researchers to construct the computer assisted diagnosis system. This tool is composed by a database with three related but independent modules: Clinical Module, Processing Module and Statistical Module.

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