Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
Author: Mei Chen
Publsiher: Academic Press
Total Pages: 230
Release: 2020-12-01
ISBN 10: 0128149736
ISBN 13: 9780128149737
Language: EN, FR, DE, ES & NL

Computer Vision for Microscopy Image Analysis Book Review:

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

Medical Optical Imaging and Virtual Microscopy Image Analysis

Medical Optical Imaging and Virtual Microscopy Image Analysis
Author: Yuankai Huo,Bryan A. Millis,Yuyin Zhou,Xiangxue Wang,Adam P. Harrison,Ziyue Xu
Publsiher: Springer Nature
Total Pages: 200
Release: 2022-09-16
ISBN 10: 3031169611
ISBN 13: 9783031169618
Language: EN, FR, DE, ES & NL

Medical Optical Imaging and Virtual Microscopy Image Analysis Book Review:

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.

Microscope Image Processing

Microscope Image Processing
Author: Qiang Wu,Fatima Merchant,Kenneth Castleman
Publsiher: Elsevier
Total Pages: 576
Release: 2010-07-27
ISBN 10: 9780080558547
ISBN 13: 0080558542
Language: EN, FR, DE, ES & NL

Microscope Image Processing Book Review:

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

Computer Vision and Machine Learning for Microscopy Image Analysis

Computer Vision and Machine Learning for Microscopy Image Analysis
Author: Carlos Federico Arteta
Publsiher: Unknown
Total Pages: 135
Release: 2015
ISBN 10: 1928374650XXX
ISBN 13: OCLC:1065077482
Language: EN, FR, DE, ES & NL

Computer Vision and Machine Learning for Microscopy Image Analysis Book Review:

Content based Microscopic Image Analysis

Content based Microscopic Image Analysis
Author: Chen Li
Publsiher: Logos Verlag Berlin GmbH
Total Pages: 196
Release: 2016-05-15
ISBN 10: 3832542531
ISBN 13: 9783832542535
Language: EN, FR, DE, ES & NL

Content based Microscopic Image Analysis Book Review:

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

Microscope Image Processing
Author: Fatima Merchant,Kenneth Castleman
Publsiher: Academic Press
Total Pages: 528
Release: 2022-09-12
ISBN 10: 0128210508
ISBN 13: 9780128210505
Language: EN, FR, DE, ES & NL

Microscope Image Processing Book Review:

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

Progress in Pattern Recognition  Image Analysis  Computer Vision  and Applications
Author: Ruben Vera-Rodriguez,Julian Fierrez,Aythami Morales
Publsiher: Springer
Total Pages: 987
Release: 2019-03-02
ISBN 10: 3030134695
ISBN 13: 9783030134693
Language: EN, FR, DE, ES & NL

Progress in Pattern Recognition Image Analysis Computer Vision and Applications Book Review:

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

Microscopic Image Analysis for Life Science Applications
Author: Jens Rittscher,Raghu Machiraju,Stephen T. C. Wong
Publsiher: Artech House
Total Pages: 489
Release: 2008
ISBN 10: 1596932376
ISBN 13: 9781596932371
Language: EN, FR, DE, ES & NL

Microscopic Image Analysis for Life Science Applications Book Review:

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.

Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
Author: S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Publsiher: Academic Press
Total Pages: 458
Release: 2017-01-18
ISBN 10: 0128104090
ISBN 13: 9780128104095
Language: EN, FR, DE, ES & NL

Deep Learning for Medical Image Analysis Book Review:

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

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
Publsiher: Springer
Total Pages: 721
Release: 2011-11-12
ISBN 10: 3642250858
ISBN 13: 9783642250859
Language: EN, FR, DE, ES & NL

Progress in Pattern Recognition Image Analysis Computer Vision and Applications Book Review:

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.

Computer Vision and Machine Intelligence in Medical Image Analysis

Computer Vision and Machine Intelligence in Medical Image Analysis
Author: Mousumi Gupta,Debanjan Konar,Siddhartha Bhattacharyya,Sambhunath Biswas
Publsiher: Springer Nature
Total Pages: 150
Release: 2019-08-28
ISBN 10: 9811387982
ISBN 13: 9789811387982
Language: EN, FR, DE, ES & NL

Computer Vision and Machine Intelligence in Medical Image Analysis Book Review:

This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.

Image Technology

Image Technology
Author: Jorge L.C. Sanz
Publsiher: Springer Science & Business Media
Total Pages: 745
Release: 2012-12-06
ISBN 10: 3642582885
ISBN 13: 9783642582882
Language: EN, FR, DE, ES & NL

Image Technology Book Review:

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.

Computer Assisted Microscopy

Computer Assisted Microscopy
Author: John C. Russ
Publsiher: Springer Science & Business Media
Total Pages: 470
Release: 2012-12-06
ISBN 10: 1461305632
ISBN 13: 9781461305637
Language: EN, FR, DE, ES & NL

Computer Assisted Microscopy Book Review:

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 be true particularly in the field of three-dimensional imaging, since new microscopy methods are beginning to be used which can produce such data. It is not the intent of this book to train programmers who will assemble their own computer systems and write their own programs. Most users require only the barest of knowledge about how to use the computer, but the greater their understanding of the various image analysis operations which are possible, their advantages and limitations, the greater the likelihood of success in their application. Likewise, the book assumes little in the way of a mathematical background, but the researcher with a secure knowledge of appropriate statistical tests will find it easier to put some of these methods into real use, and have confidence in the results, than one who has less background and experience. Supplementary texts and courses in statistics, microscopy, and specimen preparation are recommended as necessary.

Research Developments in Computer Vision and Image Processing Methodologies and Applications

Research Developments in Computer Vision and Image Processing  Methodologies and Applications
Author: Srivastava, Rajeev
Publsiher: IGI Global
Total Pages: 451
Release: 2013-09-30
ISBN 10: 1466645598
ISBN 13: 9781466645592
Language: EN, FR, DE, ES & NL

Research Developments in Computer Vision and Image Processing Methodologies and Applications Book Review:

Similar to the way in which computer vision and computer graphics act as the dual fields that connect image processing in modern computer science, the field of image processing can be considered a crucial middle road between the vision and graphics fields. Research Developments in Computer Vision and Image Processing: Methodologies and Applications brings together various research methodologies and trends in emerging areas of application of computer vision and image processing. This book is useful for students, researchers, scientists, and engineers interested in the research developments of this rapidly growing field.

New Methods to Improve Large Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty

New Methods to Improve Large Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty
Author: Stegmaier, Johannes
Publsiher: KIT Scientific Publishing
Total Pages: 266
Release: 2017-02-08
ISBN 10: 3731505908
ISBN 13: 9783731505907
Language: EN, FR, DE, ES & NL

New Methods to Improve Large Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty Book Review:

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
Publsiher: Springer Nature
Total Pages: 329
Release: 2019-12-11
ISBN 10: 9811511004
ISBN 13: 9789811511004
Language: EN, FR, DE, ES & NL

Advancement of Machine Intelligence in Interactive Medical Image Analysis Book Review:

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
Publsiher: Springer
Total Pages: 326
Release: 2017-07-12
ISBN 10: 331942999X
ISBN 13: 9783319429991
Language: EN, FR, DE, ES & NL

Deep Learning and Convolutional Neural Networks for Medical Image Computing Book Review:

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 experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

The Image Processing Handbook

The Image Processing Handbook
Author: John C. Russ
Publsiher: CRC Press
Total Pages: 885
Release: 2016-04-19
ISBN 10: 9781439840634
ISBN 13: 1439840636
Language: EN, FR, DE, ES & NL

The Image Processing Handbook Book Review:

Whether obtained by microscopes, space probes, or the human eye, the same basic tools can be applied to acquire, process, and analyze the data contained in images. Ideal for self study, The Image Processing Handbook, Sixth Edition, first published in 1992, raises the bar once again as the gold-standard reference on this subject. Using extensive new illustrations and diagrams, it offers a logically organized exploration of the important relationship between 2D images and the 3D structures they reveal. Provides Hundreds of Visual Examples in FULL COLOR! The author focuses on helping readers visualize and compare processing and measurement operations and how they are typically combined in fields ranging from microscopy and astronomy to real-world scientific, industrial, and forensic applications. Presenting methods in the order in which they would be applied in a typical workflow—from acquisition to interpretation—this book compares a wide range of algorithms used to: Improve the appearance, printing, and transmission of an image Prepare images for measurement of the features and structures they reveal Isolate objects and structures, and measure their size, shape, color, and position Correct defects and deal with limitations in images Enhance visual content and interpretation of details This handbook avoids dense mathematics, instead using new practical examples that better convey essential principles of image processing. This approach is more useful to develop readers’ grasp of how and why to apply processing techniques and ultimately process the mathematical foundations behind them. Much more than just an arbitrary collection of algorithms, this is the rare book that goes beyond mere image improvement, presenting a wide range of powerful example images that illustrate techniques involved in color processing and enhancement. Applying his 50-year experience as a scientist, educator, and industrial consultant, John Russ offers the benefit of his image processing expertise for fields ranging from astronomy and biomedical research to food science and forensics. His valuable insights and guidance continue to make this handbook a must-have reference.

Image Analysis

Image Analysis
Author: Donat P. Hader
Publsiher: CRC Press
Total Pages: 480
Release: 2000-08-23
ISBN 10: 148227390X
ISBN 13: 9781482273908
Language: EN, FR, DE, ES & NL

Image Analysis Book Review:

Automatic image analysis has become an important tool in many fields of biology, medicine, and other sciences. Since the first edition of Image Analysis: Methods and Applications, the development of both software and hardware technology has undergone quantum leaps. For example, specific mathematical filters have been developed for quality enhanceme

Progress in Pattern Recognition Image Analysis Computer Vision and Applications

Progress in Pattern Recognition  Image Analysis  Computer Vision  and Applications
Author: Ingela Nyström,Yanio Hernández Heredia,Vladimir Milián Núñez
Publsiher: Springer Nature
Total Pages: 793
Release: 2019-10-25
ISBN 10: 3030339041
ISBN 13: 9783030339043
Language: EN, FR, DE, ES & NL

Progress in Pattern Recognition Image Analysis Computer Vision and Applications Book Review:

This book constitutes the refereed conference proceedings of the 24rd Iberoamerican Congress on Pattern Recognition, CIARP 2019, held in Havana, Cuba, in October 2019. The 70 papers presented were carefully reviewed and selected from 128 submissions. The papers are organized in topical sections named: Data Mining: Natural Language Processing and Text Mining; Image Analysis and Retrieval; Machine Learning and Neural Networks; Mathematical Theory of Pattern Recognition; Pattern Recognition and Applications; Signals Analysis and Processing; Speech Recognition; Video Analysis.