Methods And Systems For Performing Segmentation And Registration Of Images Using Neutrosophic Similarity Scores
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| Author | : Yanhui Guo |
| Publisher | : Infinite Study |
| Total Pages | : 22 |
| Release | : |
| Genre | : Mathematics |
| ISBN | : |
An example method for segmenting an object contained in an image includes receiving an image including a plurality of pixels , transforming a plurality of characteristics of a pixel into respective neutrosophic set domains , calculating a neutrosophic similarity score for the pixel based on the respective neutrosophic set domains for the characteristics of the pixel , segmenting an object from background of the image using a region growing algorithm based on the neutrosophic similarity score for the pixel , and receiving a margin adjustment related to the object segmented from the background of the image .
| Author | : Florentin Smarandache |
| Publisher | : Infinite Study |
| Total Pages | : 10 |
| Release | : 2010-08-23 |
| Genre | : Mathematics |
| ISBN | : |
In this paper one generalizes the intuitionistic fuzzy set (IFS), paraconsistent set, and intuitionistic set to the neutrosophic set (NS). Many examples are presented. Distinctions between NS and IFS are underlined.
| Author | : Yanhui Guo |
| Publisher | : Academic Press |
| Total Pages | : 372 |
| Release | : 2019-08-08 |
| Genre | : Computers |
| ISBN | : 0128181494 |
Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis. - Introduces the mathematical model and concepts of neutrosophic theory and methods - Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis (CAD) systems, including approaches from soft computing and machine learning - Shows how NS techniques can be applied to medical image denoising, segmentation and classification - Provides challenges and future directions in neutrosophic set based medical image analysis
| Author | : Janmenjoy Nayak |
| Publisher | : Academic Press |
| Total Pages | : 398 |
| Release | : 2021-04-08 |
| Genre | : Science |
| ISBN | : 0128222611 |
Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques. Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis. - Presents a comprehensive handbook that covers an Introduction to Computational Intelligence in Biomedical Engineering and Healthcare, Computational Intelligence Techniques, and Advanced and Emerging Techniques in Computational Intelligence - Helps readers analyze and do advanced research in specialty healthcare applications - Includes links to websites, videos, articles and other online content to expand and support primary learning objectives
| Author | : J. Jayakumari |
| Publisher | : Springer Nature |
| Total Pages | : 837 |
| Release | : 2020-06-13 |
| Genre | : Technology & Engineering |
| ISBN | : 9811539928 |
This book presents the selected peer-reviewed papers from the International Conference on Communication Systems and Networks (ComNet) 2019. Highlighting the latest findings, ideas, developments and applications in all areas of advanced communication systems and networking, it covers a variety of topics, including next-generation wireless technologies such as 5G, new hardware platforms, antenna design, applications of artificial intelligence (AI), signal processing and optimization techniques. Given its scope, this book can be useful for beginners, researchers and professionals working in wireless communication and networks, and other allied fields.
| Author | : Juri Yanase |
| Publisher | : Infinite Study |
| Total Pages | : 51 |
| Release | : |
| Genre | : Mathematics |
| ISBN | : |
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort expended in the interface of medicine and computer science. As some CAD systems in medicine try to emulate the diagnostic decision-making process of medical experts, they can be considered as expert systems in medicine.
| Author | : Florentin Smarandache |
| Publisher | : |
| Total Pages | : 110 |
| Release | : 1998 |
| Genre | : Mathematics |
| ISBN | : |
| Author | : S. Kevin Zhou |
| Publisher | : Academic Press |
| Total Pages | : 548 |
| Release | : 2015-12-11 |
| Genre | : Computers |
| ISBN | : 0128026766 |
This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: - Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects - Methods and theories for medical image recognition, segmentation and parsing of multiple objects - Efficient and effective machine learning solutions based on big datasets - Selected applications of medical image parsing using proven algorithms - Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects - Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets - Includes algorithms for recognizing and parsing of known anatomies for practical applications
| Author | : George J Klir |
| Publisher | : World Scientific |
| Total Pages | : 842 |
| Release | : 1996-05-30 |
| Genre | : Computers |
| ISBN | : 9814499811 |
This book consists of selected papers written by the founder of fuzzy set theory, Lotfi A Zadeh. Since Zadeh is not only the founder of this field, but has also been the principal contributor to its development over the last 30 years, the papers contain virtually all the major ideas in fuzzy set theory, fuzzy logic, and fuzzy systems in their historical context. Many of the ideas presented in the papers are still open to further development. The book is thus an important resource for anyone interested in the areas of fuzzy set theory, fuzzy logic, and fuzzy systems, as well as their applications. Moreover, the book is also intended to play a useful role in higher education, as a rich source of supplementary reading in relevant courses and seminars.The book contains a bibliography of all papers published by Zadeh in the period 1949-1995. It also contains an introduction that traces the development of Zadeh's ideas pertaining to fuzzy sets, fuzzy logic, and fuzzy systems via his papers. The ideas range from his 1965 seminal idea of the concept of a fuzzy set to ideas reflecting his current interest in computing with words — a computing in which linguistic expressions are used in place of numbers.Places in the papers, where each idea is presented can easily be found by the reader via the Subject Index.
| Author | : Jan Egger |
| Publisher | : Academic Press |
| Total Pages | : 284 |
| Release | : 2021-04-29 |
| Genre | : Computers |
| ISBN | : 0128234237 |
Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives is an ideal resource for biomedical engineers and computer scientists, clinicians and clinical researchers looking for an understanding on the latest technologies applied to oral and maxillofacial surgery. In facial surgery, computer-aided decisions supplement all kind of treatment stages, from a diagnosis to follow-up examinations. This book gives an in-depth overview of state-of-the-art technologies, such as deep learning, augmented reality, virtual reality and intraoperative navigation, as applied to oral and maxillofacial surgery. It covers applications of facial surgery that are at the interface between medicine and computer science. Examples include the automatic segmentation and registration of anatomical and pathological structures, like tumors in the facial area, intraoperative navigation in facial surgery and its recent developments and challenges for treatments like zygomatic implant placement. - Provides comprehensive, state-of-the-art knowledge of interdisciplinary applications in facial surgery - Presents recent algorithmic developments like Deep Learning, along with recent devices in augmented reality and virtual reality - Includes clinical knowledge of two facials surgeons who give insights into the current clinical practice and challenges of facial surgeons in university hospitals in Austria and China
