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Neural Stem Cell Research
Among the many applications of stem cell research are nervous system diseases, diabetes, heart disease, auto-immune diseases as well as Parkinson's disease, end-stage kidney disease, liver failure, cancer, spinal cord injury, multiple sclerosis, Parkinson's disease, and Alzheimer's disease. Stem cells are self-renewing, unspecialised cells that can give rise to multiple types all of specialised cells of the body. Stem cell research also involves complex ethical and legal considerations since they involve adult, foetal tissue and embryonic sources. This book brings together leading research from throughout the world in this frontier field.
Information Technologies in Biomedicine
Information Technology in Biomedicine is an interdisciplinary research area, that bridges the gap between tethodological achievements in engineering and clinical requirements in medical diagnosis and therapy. In this book, members of the academic society of technical and medical background present their research results and clinical implementation in order to satisfy the functional requirements of authorized physicians for the benefit of the patients. An extended area is covered by the articles. It includes biomedical signals, medical image processing, computer-aided diagnosis and surgery, biometrics, healthcare and telemedicine, biomechanics, biomaterials, bioinformatics. Section on bronchoscopy presents the basis as well as new research studies performed in this field. Papers present various theoretical approaches and new methodologies based on fuzzy sets, mathematical statistics, mathematical morphology, fractals, wavelets, syntactic methods, artificial neural networks, graphs and many others.
Image and Signal Processing
This book constitutes the refereed proceedings of the Third International Conference on Image and Signal Processing, ICISP 2008, held in Cherbourg-Octeville, France, in July 2008. The 48 revised full papers and 22 revised poster papers presented were carefully reviewed and selected from 193 submissions. The papers are organized in topical sections on image filtering, image segmentation, computer vision, feature extraction, pattern recognition, graph-based representations, motion detection and estimation, new interfaces, document processing, and signal processing.
Image Analysis and Recognition
This book constitutes the thoroughly refereed proceedings of the 10th International Conference on Image Analysis and Recognition, ICIAR 2013, held in Póvoa do Varzim, Portugal, in June 2013, The 92 revised full papers presented were carefully reviewed and selected from 177 submissions. The papers are organized in topical sections on biometrics: behavioral; biometrics: physiological; classification and regression; object recognition; image processing and analysis: representations and models, compression, enhancement , feature detection and segmentation; 3D image analysis; tracking; medical imaging: image segmentation, image registration, image analysis, coronary image analysis, retinal image analysis, computer aided diagnosis, brain image analysis; cell image analysis; RGB-D camera applications; methods of moments; applications.
Advances in Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry
This book constitutes the refereed proceedings of the International Conference on Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry, MDA 2007. The topics include techniques and developments of signal and image producing procedures, object matching and object tracking in microscopic and video microscopic images, image segmentation algorithms, parallelization of image analysis and semantic tagging of images from life science applications.
Computer Vision -- ECCV 2014
The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Computer-Aided Intelligent Recognition Techniques and Applications
Intelligent recognition methods have recently proven to be indispensable in a variety of modern industries, including computer vision, robotics, medical imaging, visualization and the media. Furthermore, they play a critical role in the traditional fields such as character recognition, natural language processing and personal identification. This cutting-edge book draws together the latest findings of industry experts and researchers from around the globe. It is a timely guide for all those require comprehensive, state-of-the-art advice on the present status and future potential of intelligent recognition technology. Computer-Aided Intelligent Recognition Techniques and Applications: Provide...
Advances in Knowledge-based and Intelligent Information and Engineering Systems
In this 2012 edition of Advances in Knowledge-Based and Intelligent Information and Engineering Systems the latest innovations and advances in Intelligent Systems and related areas are presented by leading experts from all over the world. The 228 papers that are included cover a wide range of topics. One emphasis is on Information Processing, which has become a pervasive phenomenon in our civilization. While the majority of Information Processing is becoming intelligent in a very broad sense, major research in Semantics, Artificial Intelligence and Knowledge Engineering supports the domain specific applications that are becoming more and more present in our everyday living. Ontologies play a...
Machine Learning in Bioinformatics
An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalizatio...
