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Classification and Clustering in Biomed 2015 : Classification and Clustering in Biomedical Signal Processing | |||||||||||
Link: http://www.igi-global.com/publish/call-for-papers/call-details/1752 | |||||||||||
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Call For Papers | |||||||||||
Call for Chapters
Proposals Submission Deadline: June 30, 2015 Full Chapters Due: August 30, 2015 Proposal Submission Link: http://www.igi-global.com/publish/call-for-papers/submit/1752 Introduction Biomedical imaging is an essential part of early diagnosis, detection and treatment for assorted diseases, as it is considered as the first step in the proper management of medical pathological conditions. Therefore, the role of medical signal/image processing augments the ability to improve the visibility of significant features in a medical image which facilitate the diagnosis process and remove/ reduce unwanted information, etc. So, the need for powerful instruments for detecting, sorting, transmitting, analyzing, and displaying images becomes a must. Consequently, Echo Cardiograph, Magnetic Resonance Imaging (MRI), Computed Tomography (CT), X-ray, etc. are devices that encompass various paradigms dedicated to diagnosing the diseases. These instruments greatly support biologists, medical scientists, biochemists, and physicians as they produce signals and images that are required to be ambulated to extract the required features. The basic operations, such as filtering, enhancement, clustering, classification, and combining images different modalities, can assist scanning, diagnosis, research, and treatment. Thus, pattern recognition techniques play a crucial role, when applied to medical imaging by fully automating the process of indiscretion detection and maintaining the development of computer-aided diagnosis (CAD) systems. Often this involves identifying structures such as a tumor or lesions. Clustering and classification are the foremost subdivisions of pattern recognition techniques. Using these techniques, samples can be classified according to a precise property by measurements indirectly related to the property of interest. Numerous computational and cognitive applications, especially medical imaging requires objects to be grouped into disjoint sets and classification for further processing. Clustering is a statistical technique by which objects of similar nature are grouped together. Similarity means that the objects have similar shape, dimensions, magnitude, direction (vectors), color etc. Clustering achieved its importance as it is the preprocessing step in many procedures and hence there was an increasing need to make the process and its mathematical interpretations extremely simple. Then the classification rule can be used to predict the property in samples that are not part of the original training set. Consequently, there is an urgent need for edited wide collection of the major techniques of clustering and classification in the biomedical field. It compacts with methods and approaches that involve clustering, classification, pattern recognition, etc. As well as their use to support computer-aided diagnosis systems. Also, it will specify the principals of pattern recognition, medical image applications, etc. Objective This book concentrates on the foremost techniques of classification and clustering. It deals, principally, with methods and approaches that involve medical signals/image and signal analysis, image retrieval, biomedical images feature extraction, etc. and their algorithms. As well as, it will include the miscellaneous methods of different modalities in medical imaging techniques and the CAD systems. This book will endeavor to endow with significant frameworks and the latest empirical research findings in the area. It will be written for professionals who desire to improve their understanding and developing automated systems for medical imaging classification and clustering. As, the progressions of this field will help to intensify interdisciplinary discovery in medical image processing, CAD systems, medical device improvements, aid doctors and physicians in diagnosis, early detection of diseases. Target Audience The target audience of this book will be composed of professionals and researchers working in the field of medical imaging in various disciplines, e.g. Software/Hardware medical devices engineering, researchers, academicians, advanced-level students, technology developers, doctors and biologists. Furthermore, the book will provide insights and support executives concerned with recent medical image technologies that have magnetized much attention as advanced medical equipments and devoted to use medical imaging, classification and clustering. Recommended Topics Recommended topics include, but are not limited to, the following: Application of Feature Extraction on medical images Medical image classification and clustering applications Development of CAD in the medical field based on classification and clustering New trends and technologies for medical classification and Clustering. Meta-heuristics Optimization Algorithms for medical image feature extraction, classification and clustering. Principals of image processing methods Features Extraction for medical imaging Clustering and Pattern Classification Comparison of classification and clustering methods Clustering and Classification for Medical Applications Parallelization of Classification Algorithms for Medical Imaging Principals of medical images and signal analysis, including: Medical and biological imaging Concept Medical imaging and image formation (Transformation and Signal Analysis) Modern Classification Paradigm including; Wavelet transforms in medical imaging Genetic Algorithms Neural Network for medical imaging, etc. Classification and clustering paradigms for Computer-aided Diagnosis, including principles of medical imaging modalities such as: Ultrasound MRI CT X-ray Echo Cardiographs, etc. Submission Procedure Researchers and practitioners are invited to submit on or before May 30, 2015, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by June 30, 2015 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by August 30, 2015. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project. Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Classification and Clustering in Biomedical Signal Processing. All manuscripts are accepted based on a double-blind peer review editorial process. All proposals should be submitted through the E-Editorial DiscoveryTM online submission manager. Full chapters may be submitted to this book here: http://www.igi-global.com/submission/submit-chapter/?projectid=3b9e0691-418f-4194-92cd-4f028d77d10c Publisher This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit www.igi-global.com. This publication is anticipated to be released in 2017. Book Series For release in Advances in Bioinformatics and Biomedical Engineering (ABBE) book series. Series Editor(s): Ahmad Taher Azar (Benha University, Egypt) ISSN: 2327-7033 The Advances in Bioinformatics and Biomedical Engineering (ABBE) Book Series publishes research on all areas of bioinformatics and bioengineering including the development and testing of new computational methods, the management and analysis of biological data, and the implementation of novel engineering applications in all areas of medicine and biology. Through showcasing the latest in bioinformatics and biomedical engineering research, ABBE aims to be an essential resource for healthcare and medical professionals. Important Dates June 30, 2015: Proposal Submission Deadline July 31, 2015: Notification of Acceptance August 30, 2015: Full Chapter Submission October 30, 2015: Review Results Returned November 30, 2015: Revised Chapter Submission December 30, 2015: Notification of Final Acceptance Inquiries Nilanjan Dey Assistant Professor, Dept. of Computer Science, Bengal College of Engineering, West Bengal, India. Email: neelanjan.dey@gmail.com OR Amira Ashour Assistant Professor and Vice Chair of Computer Science Dep., CIT College, Taif University, KSA. Dep. of Electronics and Electrical Communication Engineering, Engineering College, Tanta Univ., Egypt. Email: amirasashour@yahoo.com |
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