Computer Vision for Microscopy Image Analysis Book

Computer Vision for Microscopy Image Analysis


  • Author : Mei Chen
  • Publisher : Academic Press
  • Release Date : 2020-12-01
  • Genre: Computers
  • Pages : 230
  • ISBN 10 : 9780128149737
  • Total Read : 63
  • File Size : 16,8 Mb

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Computer Vision for Microscopy Image Analysis Summary:

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

Content based Microscopic Image Analysis Book

Content based Microscopic Image Analysis


  • Author : Chen Li
  • Publisher : Logos Verlag Berlin GmbH
  • Release Date : 2016-05-15
  • Genre: Computers
  • Pages : 196
  • ISBN 10 : 9783832542535
  • Total Read : 99
  • File Size : 18,7 Mb

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Content based Microscopic Image Analysis Summary:

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) feature extraction, classification, and feature fusion, leading to a full-automatic approach. In this WSL approach, the problems of noisy image and object recognition are jointly resolved by a region-based classifier, and the image rotation problem is figured out through SC features. To demonstrate the usefulness and potential of the proposed methods, experiments are implemented on di erent practical biological tasks, including environmental microorganism classification, stem cell analysis, and insect tracking.

Microscope Image Processing Book

Microscope Image Processing


  • Author : Qiang Wu
  • Publisher : Elsevier
  • Release Date : 2010-07-27
  • Genre: Computers
  • Pages : 576
  • ISBN 10 : 0080558542
  • Total Read : 97
  • File Size : 10,7 Mb

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Microscope Image Processing Summary:

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 and display, object measurement and classification, autofocusing, and structured illumination. Key Features: Detailed descriptions of many leading-edge methods and algorithms In-depth analysis of the method and experimental results, taken from real-life examples Emphasis on computational and algorithmic aspects of microscope image processing Advanced material on geometric, morphological, and wavelet image processing, fluorescence, three-dimensional and time-lapse microscopy, microscope image enhancement, MultiSpectral imaging, and image data management This book is of interest to all scientists, engineers, clinicians, post-graduate fellows, and graduate students working in the fields of biology, medicine, chemistry, pharmacology, and other related fields. Anyone who uses microscopes in their work and needs to understand the methodologies and capabilities of the latest digital image processing techniques will find this book invaluable. Presents a unique practical perspective of state-of-the-art microcope image processing and the development of specialized algorithms Each chapter includes in-depth analysis of methods coupled with the results of specific real-world experiments Co-edited by Kenneth R. Castleman, world-renowned pioneer in digital image processing and author of two seminal textbooks on the subject

Deep Learning for Medical Image Analysis Book

Deep Learning for Medical Image Analysis


  • Author : S. Kevin Zhou
  • Publisher : Academic Press
  • Release Date : 2017-01-18
  • Genre: Computers
  • Pages : 458
  • ISBN 10 : 9780128104095
  • Total Read : 76
  • File Size : 11,6 Mb

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Deep Learning for Medical Image Analysis Summary:

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 learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Microscope Image Processing Book

Microscope Image Processing


  • Author : Fatima Merchant
  • Publisher : Academic Press
  • Release Date : 2022-09-12
  • Genre: Computers
  • Pages : 528
  • ISBN 10 : 9780128210505
  • Total Read : 84
  • File Size : 7,6 Mb

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Microscope Image Processing Summary:

Microscope Image Processing, Second Edition, introduces the basic fundamentals of image formation in microscopy including the importance of image digitization and display, which are key to quality visualization. Image processing and analysis are discussed in detail to provide readers with the tools necessary to improve the visual quality of images, and to extract quantitative information. Basic techniques such as image enhancement, filtering, segmentation, object measurement, and pattern recognition cover concepts integral to image processing. In addition, chapters on specific modern microscopy techniques such as fluorescence imaging, multispectral imaging, three-dimensional imaging and time-lapse imaging, introduce these key areas with emphasis on the differences among the various techniques. The new edition discusses recent developments in microscopy such as light sheet microscopy, digital microscopy, whole slide imaging, and the use of deep learning techniques for image segmentation and analysis with big data image informatics and management. Microscope Image Processing, Second Edition, is suitable for engineers, scientists, clinicians, post-graduate fellows and graduate students working in bioengineering, biomedical engineering, biology, medicine, chemistry, pharmacology and related fields, who use microscopes in their work and would like to understand the methodologies and capabilities of the latest digital image processing techniques or desire to develop their own image processing algorithms and software for specific applications. Presents a unique practical perspective of state-of-the-art microscope image processing and the development of specialized algorithms Each chapter includes in-depth analysis of methods coupled with the results of specific real-world experiments Co-edited by Kenneth R. Castleman, world-renowned pioneer in digital image processing and author of two seminal textbooks on the subject

Progress in Pattern Recognition  Image Analysis  Computer Vision  and Applications Book

Progress in Pattern Recognition Image Analysis Computer Vision and Applications


  • Author : Ruben Vera-Rodriguez
  • Publisher : Springer
  • Release Date : 2019-03-02
  • Genre: Computers
  • Pages : 987
  • ISBN 10 : 9783030134693
  • Total Read : 78
  • File Size : 16,6 Mb

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Progress in Pattern Recognition Image Analysis Computer Vision and Applications Summary:

This book constitutes the refereed post-conference proceedings of the 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018, held in Madrid, Spain, in November 2018 The 112 papers presented were carefully reviewed and selected from 187 submissions The program was comprised of 6 oral sessions on the following topics: machine learning, computer vision, classification, biometrics and medical applications, and brain signals, and also on: text and character analysis, human interaction, and sentiment analysis

Microscopic Image Analysis for Life Science Applications Book

Microscopic Image Analysis for Life Science Applications


  • Author : Jens Rittscher
  • Publisher : Artech House
  • Release Date : 2008
  • Genre: Medical
  • Pages : 489
  • ISBN 10 : 9781596932371
  • Total Read : 64
  • File Size : 6,8 Mb

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Microscopic Image Analysis for Life Science Applications Summary:

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.

Medical Optical Imaging and Virtual Microscopy Image Analysis Book

Medical Optical Imaging and Virtual Microscopy Image Analysis


  • Author : Yuankai Huo
  • Publisher : Springer Nature
  • Release Date : 2022-09-16
  • Genre: Computers
  • Pages : 200
  • ISBN 10 : 9783031169618
  • Total Read : 72
  • File Size : 14,9 Mb

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Medical Optical Imaging and Virtual Microscopy Image Analysis Summary:

This book constitutes the refereed proceedings of the 1st International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis, MOVI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, in Singapore, Singapore, in September 2022. The 18 papers presented at MOVI 2022 were carefully reviewed and selected from 25 submissions. The objective of the MOVI workshop is to promote novel scalable and resource-efficient medical image analysis algorithms for high-dimensional image data analy-sis, from optical imaging to virtual microscopy.