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The last few years have seen a great increase in the amount of data available to scientists. Datasets with millions of objects and hundreds, if not thousands of measurements are now commonplace in many disciplines. However, many of the computational techniques used to analyse this data cannot cope with such large datasets. Therefore, strategies need to be employed as a pre-processing step to reduce the number of objects, or measurements, whilst retaining important information inherent to the data. Spectral dimensionality reduction is one such family of methods that has proven to be an indispensable tool in the data processing pipeline. In recent years the area has gained much attention thanks to the development of nonlinear spectral dimensionality reduction methods, often referred to as manifold learning algorithms. Numerous algorithms and improvements have been proposed for the purpose of performing spectral dimensionality reduction, yet there is still no gold standard technique. Those wishing to use spectral dimensionality reduction without prior knowledge of the field will immediately be confronted with questions that need answering: What parameter values to use? How many dimensions should the data be embedded into? How are new data points incorporated? What about large-scale data? For many, a search of the literature to find answers to these questions is impractical, as such, there is a need for a concise discussion into the problems themselves, how they affect spectral dimensionality reduction, and how these problems can be overcome. This book provides a survey and reference aimed at advanced undergraduate and postgraduate students as well as researchers, scientists, and engineers in a wide range of disciplines. Dimensionality reduction has proven useful in a wide range of problem domains and so this book will be applicable to anyone with a solid grounding in statistics and computer science seeking to apply spectral dimensionality to their work.

Database management. --- Dimension reduction (Statistics) --- Dimensional analysis. --- Dimensionality reduction (Statistics) --- Reduction, Dimension (Statistics) --- Reduction, Dimensionality (Statistics) --- Computer science. --- Data structures (Computer science). --- Algorithms. --- Artificial intelligence. --- Image processing. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Data Structures. --- Algorithm Analysis and Problem Complexity. --- Image Processing and Computer Vision. --- Statistics --- Physical measurements --- Data structures (Computer scienc. --- Computer software. --- Computer vision. --- Artificial Intelligence. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Software, Computer --- Computer systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data structures (Computer science) --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Algorism --- Algebra --- Arithmetic --- Optical equipment --- Foundations --- Computer science --- Mathematics.

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This book constitutes the refereed proceedings of the 22st Annual Conference on Medical Image Understanding and Analysis, MIUA 2018, held in Southampton, UK, in July 2018. The 34 revised full papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on liver analysis, medical image analysis, texture and image analysis, MRI: applications and techniques, segmentation in medical images, CT: learning and planning, ocular imaging analysis, applications of medical image analysis.

Computer science. --- Artificial intelligence. --- Image processing. --- Computer Science. --- Image Processing and Computer Vision. --- Artificial Intelligence (incl. Robotics). --- Computer vision. --- Artificial Intelligence. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Diagnostic imaging --- Data processing --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment

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This volume of Springer’s Lecture Notes in Computer Science series records th the proceedings of the 8 International Workshop on Digital Mammography (IWDM), which was held in Manchester, UK, June 18–21, 2006. The meetings bring together a diverse set of researchers (physicists, mathematicians, computer scientists, engineers), clinicians (radiologists, surgeons) and representatives of industry, who are jointly committed to developing technology, not just for its own sake, but to support clinicians in the early detection and subsequent patient management of breast cancer. The conference series was initiated at a 1993 meeting of the SPIE in San Jose, with subsequent meetings hosted every two years by researchers around the world. Previous meetings were held in York, Chicago, Nijmegen, Toronto, Bremen, and North Carolina. It is interesting to reflect on the changes that have occurred during the past 13 years. Then, the dominant technology was ?lm-screen mammography; now it is full-field digital mammography. Then, there were few screening programmes world-wide; now there are many. Then, there was the hope that computer-aided detection (CAD) of early signs of cancer might be possible; now CAD is not only a reality but (more importantly) a commercially led clinical reality. Then, algorithmswerealmostentirelyheuristicwithlittleclinicalsupport;nowthereis arequirementforsubstantialclinicalsupportforanyalgorithmthatisdeveloped and published. However, upon reflection, could we have predicted with absolute certainty what would be the key questions to be addressed over the subsequent (say) six years? No! That is the nature, joy, and frustration of research. There are more blind alleys to explore than there are rich veins that bring gold (in all senses of that analogy!).

Breast --- Radiography, Medical --- Sein --- Radiography --- Congresses. --- Digital techniques --- Cancer --- Diagnosis --- Diagnostic --- Congrès --- Radiographic Image Enhancement --- Breast Neoplasms --- Radiographic Image Interpretation, Computer-Assisted --- Mammography --- Image Enhancement --- Image Interpretation, Computer-Assisted --- Neoplasms by Site --- Breast Diseases --- Diagnostic Imaging --- Photography --- Image Processing, Computer-Assisted --- Diagnosis, Computer-Assisted --- Skin Diseases --- Neoplasms --- Decision Making, Computer-Assisted --- Diseases --- Diagnostic Techniques and Procedures --- Skin and Connective Tissue Diseases --- Computing Methodologies --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Information Science --- Medical Informatics Applications --- Medical Informatics --- Applied Physics --- Gynecology & Obstetrics --- Engineering & Applied Sciences --- Medicine --- Health & Biological Sciences --- Data processing --- Breasts --- Computer science. --- Health informatics. --- Radiology. --- Information storage and retrieval. --- Image processing. --- Pattern recognition. --- Bioinformatics. --- Computer Science. --- Image Processing and Computer Vision. --- Health Informatics. --- Imaging / Radiology. --- Information Storage and Retrieval. --- Pattern Recognition. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Radiological physics --- Physics --- Radiation --- Clinical informatics --- Health informatics --- Medical information science --- Informatics --- Science --- Chest --- Large-breasted women --- Computer vision. --- Medical records --- Radiology, Medical. --- Information storage and retrieva. --- Optical pattern recognition. --- Data processing. --- Pattern perception --- Perceptrons --- Visual discrimination --- Clinical radiology --- Radiology, Medical --- Radiology (Medicine) --- Medical physics --- EHR systems --- EHR technology --- EHRs (Electronic health records) --- Electronic health records --- Electronic medical records --- EMR systems --- EMRs (Electronic medical records) --- Information storage and retrieval systems --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Medical care --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Optical data processing. --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment

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This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018, held in Funchal, Madeira, Portugal, in January 2018. The 25 revised full papers presented were carefully reviewed and selected from a total of 299 submissions. The papers are organized in topical sections on biomedical electronics and devices; bioimaging; bioinformatics models, methods and algorithms; health informatics.

Medical records --- Artificial intelligence. --- Computer vision. --- Computer Communication Networks. --- Software engineering. --- Computer security. --- Health Informatics. --- Artificial Intelligence. --- Image Processing and Computer Vision. --- Software Engineering. --- Systems and Data Security. --- Data processing. --- Computer privacy --- Computer system security --- Computer systems --- Computers --- Cyber security --- Cybersecurity --- Electronic digital computers --- Protection of computer systems --- Security of computer systems --- Data protection --- Security systems --- Hacking --- Computer software engineering --- Engineering --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- EHR systems --- EHR technology --- EHRs (Electronic health records) --- Electronic health records --- Electronic medical records --- EMR systems --- EMRs (Electronic medical records) --- Information storage and retrieval systems --- Protection --- Security measures --- Medical care --- Medical informatics. --- Biomedical materials. --- Clinical informatics --- Health informatics --- Medical information science --- Information science --- Medicine --- Biocompatible materials --- Biomaterials --- Medical materials --- Biomedical engineering --- Materials --- Biocompatibility --- Prosthesis --- Data processing --- Health informatics. --- Optical data processing. --- Computer communication systems. --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Distributed processing --- Optical equipment