Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Computational Topology For Biomedical Image And Data Analysis
Download Computational Topology For Biomedical Image And Data Analysis full books in PDF, epub, and Kindle. Read online Computational Topology For Biomedical Image And Data Analysis ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Computational Topology for Biomedical Image and Data Analysis by : Rodrigo Rojas Moraleda
Download or read book Computational Topology for Biomedical Image and Data Analysis written by Rodrigo Rojas Moraleda and published by CRC Press. This book was released on 2019-07-12 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an accessible yet rigorous introduction to topology and homology focused on the simplicial space. It presents a compact pipeline from the foundations of topology to biomedical applications. It will be of interest to medical physicists, computer scientists, and engineers, as well as undergraduate and graduate students interested in this topic. Features: Presents a practical guide to algebraic topology as well as persistence homology Contains application examples in the field of biomedicine, including the analysis of histological images and point cloud data
Book Synopsis Research in Computational Topology by : Erin Wolf Chambers
Download or read book Research in Computational Topology written by Erin Wolf Chambers and published by Springer. This book was released on 2018-07-30 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the first Workshop for Women in Computational Topology that took place in 2016, this volume assembles new research and applications in computational topology. Featured articles range over the breadth of the discipline, including topics such as surface reconstruction, topological data analysis, persistent homology, algorithms, and surface-embedded graphs. Applications in graphics, medical imaging, and GIS are discussed throughout the book. Four of the papers in this volume are the product of working groups that were established and developed during the workshop. Additional papers were also solicited from the broader Women in Computational Topology network. The volume is accessible to a broad range of researchers, both within the field of computational topology and in related disciplines such as statistics, computational biology, and machine learning.
Book Synopsis Computational Topology for Data Analysis by : Tamal Krishna Dey
Download or read book Computational Topology for Data Analysis written by Tamal Krishna Dey and published by Cambridge University Press. This book was released on 2022-03-10 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Topological data analysis (TDA) has emerged recently as a viable tool for analyzing complex data, and the area has grown substantially both in its methodologies and applicability. Providing a computational and algorithmic foundation for techniques in TDA, this comprehensive, self-contained text introduces students and researchers in mathematics and computer science to the current state of the field. The book features a description of mathematical objects and constructs behind recent advances, the algorithms involved, computational considerations, as well as examples of topological structures or ideas that can be used in applications. It provides a thorough treatment of persistent homology together with various extensions – like zigzag persistence and multiparameter persistence – and their applications to different types of data, like point clouds, triangulations, or graph data. Other important topics covered include discrete Morse theory, the Mapper structure, optimal generating cycles, as well as recent advances in embedding TDA within machine learning frameworks.
Book Synopsis Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data by : Mauricio Reyes
Download or read book Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data written by Mauricio Reyes and published by Springer Nature. This book was released on 2021-09-21 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, and the First International Workshop on Topological Data Analysis and Its Applications for Medical Data, TDA4MedicalData 2021, held on September 27, 2021, in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021. The 7 full papers presented at iMIMIC 2021 and 5 full papers held at TDA4MedicalData 2021 were carefully reviewed and selected from 12 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. TDA4MedicalData is focusing on using TDA techniques to enhance the performance, generalizability, efficiency, and explainability of the current methods applied to medical data.
Book Synopsis Advances in Computational Techniques for Biomedical Image Analysis by : Deepika Koundal
Download or read book Advances in Computational Techniques for Biomedical Image Analysis written by Deepika Koundal and published by Academic Press. This book was released on 2020-05-28 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation. Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems. Covers various challenges and common research issues related to biomedical image analysis Describes advanced computational approaches for biomedical image analysis Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization Explores cloud based medical imaging together with medical imaging security and forensics
Book Synopsis Computer Vision for Biomedical Image Applications by : Yanxi Liu
Download or read book Computer Vision for Biomedical Image Applications written by Yanxi Liu and published by Springer Science & Business Media. This book was released on 2005-10-10 with total page 577 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends, CVBIA 2005, held in Beijing, China, in October 2005 within the scope of ICCV 20.
Book Synopsis Medical Image Analysis by : Alejandro Frangi
Download or read book Medical Image Analysis written by Alejandro Frangi and published by Academic Press. This book was released on 2023-09-20 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. Provides an authoritative description of key concepts and methods Includes tutorial-based sections that clearly explain principles and their application to different medical domains Presents a representative selection of topics to match a modern and relevant approach to medical image computing
Book Synopsis 3D Image Reconstruction for CT and PET by : Daniele Panetta
Download or read book 3D Image Reconstruction for CT and PET written by Daniele Panetta and published by CRC Press. This book was released on 2020-10-11 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a practical guide to tomographic image reconstruction with projection data, with strong focus on Computed Tomography (CT) and Positron Emission Tomography (PET). Classic methods such as FBP, ART, SIRT, MLEM and OSEM are presented with modern and compact notation, with the main goal of guiding the reader from the comprehension of the mathematical background through a fast-route to real practice and computer implementation of the algorithms. Accompanied by example data sets, real ready-to-run Python toolsets and scripts and an overview the latest research in the field, this guide will be invaluable for graduate students and early-career researchers and scientists in medical physics and biomedical engineering who are beginners in the field of image reconstruction. A top-down guide from theory to practical implementation of PET and CT reconstruction methods, without sacrificing the rigor of mathematical background Accompanied by Python source code snippets, suggested exercises, and supplementary ready-to-run examples for readers to download from the CRC Press website Ideal for those willing to move their first steps on the real practice of image reconstruction, with modern scientific programming language and toolsets Daniele Panetta is a researcher at the Institute of Clinical Physiology of the Italian National Research Council (CNR-IFC) in Pisa. He earned his MSc degree in Physics in 2004 and specialisation diploma in Health Physics in 2008, both at the University of Pisa. From 2005 to 2007, he worked at the Department of Physics "E. Fermi" of the University of Pisa in the field of tomographic image reconstruction for small animal imaging micro-CT instrumentation. His current research at CNR-IFC has as its goal the identification of novel PET/CT imaging biomarkers for cardiovascular and metabolic diseases. In the field micro-CT imaging, his interests cover applications of three-dimensional morphometry of biosamples and scaffolds for regenerative medicine. He acts as reviewer for scientific journals in the field of Medical Imaging: Physics in Medicine and Biology, Medical Physics, Physica Medica, and others. Since 2012, he is adjunct professor in Medical Physics at the University of Pisa. Niccolò Camarlinghi is a researcher at the University of Pisa. He obtained his MSc in Physics in 2007 and his PhD in Applied Physics in 2012. He has been working in the field of Medical Physics since 2008 and his main research fields are medical image analysis and image reconstruction. He is involved in the development of clinical, pre-clinical PET and hadron therapy monitoring scanners. At the time of writing this book he was a lecturer at University of Pisa, teaching courses of life-sciences and medical physics laboratory. He regularly acts as a referee for the following journals: Medical Physics, Physics in Medicine and Biology, Transactions on Medical Imaging, Computers in Biology and Medicine, Physica Medica, EURASIP Journal on Image and Video Processing, Journal of Biomedical and Health Informatics.
Book Synopsis Medical Physics During the COVID-19 Pandemic by : Kwan Hoong Ng
Download or read book Medical Physics During the COVID-19 Pandemic written by Kwan Hoong Ng and published by CRC Press. This book was released on 2021-03-28 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to cover the impact of COVID-19 on the field of medical physics Edited by two experts in the field, with chapter contributions from subject area specialists around the world Broad, global coverage, ranging from the impact on teaching, research, and publishing, with unique perspectives from journal editors and students and trainees
Book Synopsis Computational Topology in Image Context by : Alexandra Bac
Download or read book Computational Topology in Image Context written by Alexandra Bac and published by Springer. This book was released on 2016-06-01 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 6th International Workshop on Computational Topology in Image Context, CTIC 2016, held in Marseille, France, in June 2016. The 24 papers presented in this volume were carefully reviewed and selected from 35 submissions. Additionally, this volume contains 2 invited papers. CTIC covers a wide range of topics such as: topological invariants and their computation, homology, cohomology, linking number, fundamental groups; algorithm optimization in discrete geometry, transfer of mathematical tools, parallel computation in multi-dimensional volume context, hierarchical approaches; experimental evaluation of algorithms and heuristics; combinatorial or multi-resolution models; discrete or computational topology; geometric modeling guided by topological constraints; computational topological dynamics; and use of topological information in discrete geometry applications.
Book Synopsis Computational Homology by : Tomasz Kaczynski
Download or read book Computational Homology written by Tomasz Kaczynski and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Homology is a powerful tool used by mathematicians to study the properties of spaces and maps that are insensitive to small perturbations. This book uses a computer to develop a combinatorial computational approach to the subject. The core of the book deals with homology theory and its computation. Following this is a section containing extensions to further developments in algebraic topology, applications to computational dynamics, and applications to image processing. Included are exercises and software that can be used to compute homology groups and maps. The book will appeal to researchers and graduate students in mathematics, computer science, engineering, and nonlinear dynamics.
Book Synopsis Computational Topology in Image Context by : Rebeca Marfil
Download or read book Computational Topology in Image Context written by Rebeca Marfil and published by Springer. This book was released on 2019-01-10 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International Workshop on Computational Topology in Image Context, CTIC 2019, held in Málaga, Spain, in January 2019. The 14 papers presented in this volume were carefully reviewed and selected from 21 submissions. Papers deal with theoretical issues but most of them put the attention on the applicability of concepts and algorithms. These were designed to deal with objects and images, but also with the speech signal. The final application must be for instance in the medical domain or in the robotics one.
Author :Thomas Martin Deserno Publisher :Springer Science & Business Media ISBN 13 :3642158161 Total Pages :595 pages Book Rating :4.6/5 (421 download)
Book Synopsis Biomedical Image Processing by : Thomas Martin Deserno
Download or read book Biomedical Image Processing written by Thomas Martin Deserno and published by Springer Science & Business Media. This book was released on 2011-03-01 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.
Book Synopsis Topological Data Analysis by : Nils A. Baas
Download or read book Topological Data Analysis written by Nils A. Baas and published by Springer Nature. This book was released on 2020-06-25 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 2018 Abel Symposium, which was held in Geiranger, Norway, on June 4-8, 2018. The symposium offered an overview of the emerging field of "Topological Data Analysis". This volume presents papers on various research directions, notably including applications in neuroscience, materials science, cancer biology, and immune response. Providing an essential snapshot of the status quo, it represents a valuable asset for practitioners and those considering entering the field.
Book Synopsis Biomedical Image Analysis by : Scott Acton
Download or read book Biomedical Image Analysis written by Scott Acton and published by Morgan & Claypool Publishers. This book was released on 2009-03-08 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models, and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation
Book Synopsis Topology in Real-World Machine Learning and Data Analysis by : Kathryn Hess
Download or read book Topology in Real-World Machine Learning and Data Analysis written by Kathryn Hess and published by Frontiers Media SA. This book was released on 2022-11-07 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning and Medical Imaging by : Guorong Wu
Download or read book Machine Learning and Medical Imaging written by Guorong Wu and published by Academic Press. This book was released on 2016-08-11 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics Features self-contained chapters with a thorough literature review Assesses the development of future machine learning techniques and the further application of existing techniques
