Computer Vision for Microscopy Image Analysis

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  • Author : Mei Chen
  • Publisher : Academic Press
  • Pages : 228 pages
  • ISBN : 0128149736
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Computer Vision for Microscopy Image Analysis

Download or Read online Computer Vision for Microscopy Image Analysis full in PDF, ePub and kindle. this book written by Mei Chen and published by Academic Press which was released on 01 December 2020 with total page 228 pages. We cannot guarantee that Computer Vision for Microscopy Image Analysis book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will advance your efforts. Progress in imaging techniques has enabled the acquisition of large volumes of microscopy data and made it possible to conduct large-scale, image-based experiments for biomedical discovery. The main challenge and bottleneck in such experiments is the conversion of "big visual data" into interpretable information. Visual analysis of large-scale microscopy data is a daunting task. Computer vision has the potential to automate this task. One key advantage is that computers perform analysis more reproducibly and less subjectively than human annotators. Moreover, high-throughput microscopy calls for effective and efficient techniques as there are not enough human resources to advance science by manual annotation. This book articulates the strong need for biologists and computer vision experts to collaborate to overcome the limits of human visual perception, and devotes a chapter each to the major steps in analyzing microscopy images, such as detection and segmentation, classification, tracking, and event detection. Discover how computer vision can automate and enhance the human assessment of microscopy images for discovery Grasp the state-of-the-art approaches, especially deep neural networks Learn where to obtain open-source datasets and software to jumpstart his or her own investigation

Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
  • Author : Mei Chen
  • Publisher : Academic Press
  • Release : 01 December 2020
GET THIS BOOK Computer Vision for Microscopy Image Analysis

Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will advance your efforts. Progress in imaging techniques has enabled the acquisition of large volumes of microscopy data and made it possible to conduct large-scale, image-based experiments for biomedical discovery. The

Content based Microscopic Image Analysis

Content based Microscopic Image Analysis
  • Author : Chen Li
  • Publisher : Logos Verlag Berlin GmbH
  • Release : 15 May 2016
GET THIS BOOK Content based Microscopic Image Analysis

In this dissertation, novel Content-based Microscopic Image Analysis (CBMIA) methods, including Weakly Supervised Learning (WSL), are proposed to aid biological studies. In a CBMIA task, noisy image, image rotation, and object recognition problems need to be addressed. To this end, the first approach is a general supervised learning method, which consists of image segmentation, shape feature extraction, classification, and feature fusion, leading to a semi-automatic approach. In contrast, the second approach is a WSL method, which contains Sparse Coding (SC)

Microscope Image Processing

Microscope Image Processing
  • Author : Qiang Wu,Fatima Merchant,Kenneth Castleman
  • Publisher : Elsevier
  • Release : 27 July 2010
GET THIS BOOK Microscope Image Processing

Digital image processing, an integral part of microscopy, is increasingly important to the fields of medicine and scientific research. This book provides a unique one-stop reference on the theory, technique, and applications of this technology. Written by leading experts in the field, this book presents a unique practical perspective of state-of-the-art microscope image processing and the development of specialized algorithms. It contains in-depth analysis of methods coupled with the results of specific real-world experiments. Microscope Image Processing covers image digitization

Image Technology

Image Technology
  • Author : Jorge L.C. Sanz
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOK Image Technology

Image processing and machine vision are fields of renewed interest in the commercial market. People in industry, managers, and technical engineers are looking for new technologies to move into the market. Many of the most promising developments are taking place in the field of image processing and its applications. The book offers a broad coverage of advances in a range of topics in image processing and machine vision.

Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
  • Author : S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
  • Publisher : Academic Press
  • Release : 18 January 2017
GET THIS BOOK Deep Learning for Medical Image Analysis

Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great

Microscopic Image Analysis for Life Science Applications

Microscopic Image Analysis for Life Science Applications
  • Author : Jens Rittscher,Raghu Machiraju,Stephen T. C. Wong
  • Publisher : Artech House
  • Release : 04 July 2022
GET THIS BOOK Microscopic Image Analysis for Life Science Applications

This unique resource gives you a detailed understanding of imaging platforms, fluorescence imaging, and fundamental image processing algorithms. Further, it guides you through application of advanced image analysis methods and techniques to specific biological problems. The book presents applications that span a wide range of scales, from the detection of signaling events in sub-cellular structures, to the automated analysis of tissue structures.

Progress in Pattern Recognition Image Analysis Computer Vision and Applications

Progress in Pattern Recognition  Image Analysis  Computer Vision  and Applications
  • Author : César San Martin,Sang-Woon Kim
  • Publisher : Springer
  • Release : 12 November 2011
GET THIS BOOK Progress in Pattern Recognition Image Analysis Computer Vision and Applications

This book constitutes the refereed proceedings of the 16th Iberoamerican Congress on Pattern Recognition, CIARP 2011, held in Pucón, Chile, in November 2011. The 81 revised full papers presented together with 3 keynotes were carefully reviewed and selected from numerous submissions. Topics of interest covered are image processing, restoration and segmentation; computer vision; clustering and artificial intelligence; pattern recognition and classification; applications of pattern recognition; and Chilean Workshop on Pattern Recognition.

Biomedical Image Synthesis and Simulation

Biomedical Image Synthesis and Simulation
  • Author : Ninon Burgos,David Svoboda
  • Publisher : Academic Press
  • Release : 30 June 2022
GET THIS BOOK Biomedical Image Synthesis and Simulation

Biomedical Image Synthesis and Simulations: Methods and Applications presents the latest on basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. Sections introduce and describe the simulation and synthesis methods that were developed and successfully used within the last twenty years and give examples of successful applications of these methods. As the book provides a survey of all the commonly established approaches and more recent deep learning methods, it is highly suitable for graduate

Computer Assisted Microscopy

Computer Assisted Microscopy
  • Author : John C. Russ
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOK Computer Assisted Microscopy

The use of computer-based image analysis systems for all kinds of images, but especially for microscope images, has become increasingly widespread in recent years, as computer power has increased and costs have dropped. Software to perform each of the various tasks described in this book exists now, and without doubt additional algorithms to accomplish these same things more efficiently, and to perform new kinds of image processing, feature discrimination and measurement, will continue to be developed. This is likely to

Data Engineering and Communication Technology

Data Engineering and Communication Technology
  • Author : K. Srujan Raju,Roman Senkerik,Satya Prasad Lanka,V. Rajagopal
  • Publisher : Springer Nature
  • Release : 08 January 2020
GET THIS BOOK Data Engineering and Communication Technology

This book includes selected papers presented at the 3rd International Conference on Data Engineering and Communication Technology (ICDECT-2K19), held at Stanley College of Engineering and Technology for Women, Hyderabad, from 15 to 16 March 2019. It features advanced, multidisciplinary research towards the design of smart computing, information systems, and electronic systems. It also focuses on various innovation paradigms in system knowledge, intelligence, and sustainability which can be applied to provide viable solutions to diverse problems related to society, the environment, and industry.

Neutrosophic Set in Medical Image Analysis

Neutrosophic Set in Medical Image Analysis
  • Author : Yanhui Guo,Amira S. Ashour
  • Publisher : Academic Press
  • Release : 08 August 2019
GET THIS BOOK Neutrosophic Set in Medical Image Analysis

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

Advancement of Machine Intelligence in Interactive Medical Image Analysis

Advancement of Machine Intelligence in Interactive Medical Image Analysis
  • Author : Om Prakash Verma,Sudipta Roy,Subhash Chandra Pandey,Mamta Mittal
  • Publisher : Springer Nature
  • Release : 11 December 2019
GET THIS BOOK Advancement of Machine Intelligence in Interactive Medical Image Analysis

The book discusses major technical advances and research findings in the field of machine intelligence in medical image analysis. It examines the latest technologies and that have been implemented in clinical practice, such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy. This book provides insights into the basic science involved in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.

Deep Learning and Convolutional Neural Networks for Medical Image Computing

Deep Learning and Convolutional Neural Networks for Medical Image Computing
  • Author : Le Lu,Yefeng Zheng,Gustavo Carneiro,Lin Yang
  • Publisher : Springer
  • Release : 12 July 2017
GET THIS BOOK Deep Learning and Convolutional Neural Networks for Medical Image Computing

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research