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Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
A Book

by Mei Chen, Ph.D

  • Publisher : Academic Press
  • Release : 2019-02-15
  • Pages : 350
  • ISBN : 9780128149720
  • Language : En, Es, Fr & De
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Computer Vision for Microscopy Image Analysis provides a broad and in-depth introduction to state-of-the-art computer vision techniques for microscopy image analysis, showing how they can be applied to biological and medical data. Topics covered include sections on how computer vision analysis can automate and enhance human assessment of microscopy images for discovery, the important steps in microscopy image analysis, state-of-the-art methods for microscopy image analysis, how high-throughput microscopy enables researchers to automatically acquire thousands of images over a matter of hours, and more. Contains a general overview on each topics that is followed by an in-depth presentation of a state-of-the-art approach Includes perspectives and content contributed by both technologists and biologists Covers specific problems of segmentation and mitosis detection Introduces the fundamentals of tracking and 3D analysis Presents open source data and toolsets for microscopy image analysis on an accompanying website

Computer Vision Approaches to Medical Image Analysis

Computer Vision Approaches to Medical Image Analysis
Second International ECCV Workshop, CVAMIA 2006, Graz, Austria, May 12, 2006, Revised Papers

by Reinhard R. Beichel

  • Publisher : Springer Science & Business Media
  • Release : 2006-09-29
  • Pages : 262
  • ISBN : 3540462570
  • Language : En, Es, Fr & De
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Medical imaging and medical image analysis are developing rapidly. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to su?er from a lack of reproducibility. A signi?cant researche?ort is devoted to developing algorithms for processing the wealth of data available and extracting the relevant information in a computerized and quantitative fashion. Medical imaging and image analysis are interdisciplinary areas combining electrical, computer, and biomedical engineering; computer science; mathem- ics; physics; statistics; biology; medicine; and other ?elds. Medical imaging and computer vision, interestingly enough, have developed and continue developing somewhat independently. Nevertheless, bringing them together promises to b- e?t both of these ?elds. This was the second time that a satellite workshop,solely devoted to medical image analysis issues, was held in conjunction with the European Conference on Computer Vision (ECCV), and we are optimistic that this will become a tradition at ECCV. We received 38 full-length paper submissions to the second Computer Vision Approaches to Medical Image Analysis (CVAMIA) Workshop, out of which 10 were accepted for oral and 11 for poster presentation after a rigorous peer-review process. In addition, the workshop included three invited talks. The ?rst was given by Maryellen Giger from the University of Chicago, USA — titled “Multi-Modality Breast CADx”.

Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
A Book

by Mei Chen

  • Publisher : Academic Press
  • Release : 2020-12-01
  • Pages : 228
  • ISBN : 0128149736
  • Language : En, Es, Fr & De
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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 and Machine Learning for Microscopy Image Analysis

Computer Vision and Machine Learning for Microscopy Image Analysis
A Book

by Carlos Federico Arteta

  • Publisher : Unknown Publisher
  • Release : 2015
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
A Book

by S. Kevin Zhou,Hayit Greenspan,Dinggang Shen

  • Publisher : Academic Press
  • Release : 2017-01-18
  • Pages : 458
  • ISBN : 0128104090
  • Language : En, Es, Fr & De
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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

Computer Vision and Machine Intelligence in Medical Image Analysis

Computer Vision and Machine Intelligence in Medical Image Analysis
International Symposium, ISCMM 2019

by Mousumi Gupta,Debanjan Konar,Siddhartha Bhattacharyya,Sambhunath Biswas

  • Publisher : Springer Nature
  • Release : 2019-08-28
  • Pages : 150
  • ISBN : 9811387982
  • Language : En, Es, Fr & De
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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
Advances in Image Processing, Multimedia and Machine Vision

by Jorge L.C. Sanz

  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • Pages : 745
  • ISBN : 3642582885
  • Language : En, Es, Fr & De
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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.

Microscope Image Processing

Microscope Image Processing
A Book

by Qiang Wu,Fatima Merchant,Kenneth Castleman

  • Publisher : Elsevier
  • Release : 2010-07-27
  • Pages : 576
  • ISBN : 9780080558547
  • Language : En, Es, Fr & De
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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

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
23rd Iberoamerican Congress, CIARP 2018, Madrid, Spain, November 19-22, 2018, Proceedings

by Ruben Vera-Rodriguez,Julian Fierrez,Aythami Morales

  • Publisher : Springer
  • Release : 2019-03-02
  • Pages : 987
  • ISBN : 3030134695
  • Language : En, Es, Fr & De
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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

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
16th Iberoamerican Congress on Pattern Recognition, CIARP 2011, Pucón, Chile, November 15-18, 2011. Proceedings

by César San Martin,Sang-Woon Kim

  • Publisher : Springer
  • Release : 2011-11-12
  • Pages : 721
  • ISBN : 3642250858
  • Language : En, Es, Fr & De
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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.

Microscopic Image Analysis for Life Science Applications

Microscopic Image Analysis for Life Science Applications
A Book

by Jens Rittscher,Raghu Machiraju,Stephen T. C. Wong

  • Publisher : Artech House
  • Release : 2008
  • Pages : 489
  • ISBN : 1596932376
  • Language : En, Es, Fr & De
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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
15th Iberoamerican Congress on Pattern Recognition, CIARP 2010, Sao Paulo, Brazil, November 8-11, 2010, Proceedings

by Isabelle Bloch,Roberto M. Cesar, Jr.

  • Publisher : Springer
  • Release : 2010-11-02
  • Pages : 571
  • ISBN : 3642166873
  • Language : En, Es, Fr & De
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Pattern recognition is a central topic in contemporary computer sciences, with continuously evolving topics, challenges, and methods, including machine learning, content-based image retrieval, and model- and knowledge-based - proaches, just to name a few. The Iberoamerican Congress on Pattern Recog- tion (CIARP) has become established as a high-quality conference, highlighting the recent evolution of the domain. These proceedings include all papers presented during the 15th edition of this conference, held in Sao Paulo, Brazil, in November 2010. As was the case for previous conferences, CIARP 2010 attracted parti- pants from around the world with the aim of promoting and disseminating - going research on mathematical methods and computing techniques for pattern recognition, computer vision, image analysis, and speech recognition, as well as their applications in such diverse areas as robotics, health, entertainment, space exploration, telecommunications, data mining, document analysis, and natural language processing and recognition, to name only a few of them. Moreover, it provided a forum for scienti?c research, experience exchange, sharing new kno- edge and increasing cooperation between research groups in pattern recognition and related areas. It is important to underline that these conferences have contributed sign- icantly to the growth of national associations for pattern recognition in the Iberoamerican region, all of them as members of the International Association for Pattern Recognition (IAPR).

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
18th Iberoamerican Congress, CIARP 2013, Havana, Cuba, November 20-13, 2013, Proceedings

by José Ruiz-Shulcloper,Gabriella Sanniti di Baja

  • Publisher : Springer
  • Release : 2013-11-04
  • Pages : 573
  • ISBN : 3642418279
  • Language : En, Es, Fr & De
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The two-volume set LNCS 8258 and 8259 constitutes the refereed proceedings of the 18th Iberoamerican Congress on Pattern Recognition, CIARP 2013, held in Havana, Cuba, in November 2013. The 137 papers presented, together with two keynotes, were carefully reviewed and selected from 262 submissions. The papers are organized in topical sections on mathematical theory of PR, supervised and unsupervised classification, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern recognition, biometrics, video analysis, and data mining.

Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis

Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis
ECCV 2004 Workshops CVAMIA and MMBIA Prague, Czech Republic, May 15, 2004, Revised Selected Papers

by Milan Sonka,Ioannis A. Kakadiaris,Jan Kybic

  • Publisher : Springer Science & Business Media
  • Release : 2004-09-20
  • Pages : 444
  • ISBN : 3540226753
  • Language : En, Es, Fr & De
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Medical imaging and medical image analysisare rapidly developing. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to su?er from a lack of reproducibility. A signi?cant researche?ort is devoted to developing algorithms for processing the wealth of data available and extracting the relevant information in a computerized and quantitative fashion. Medical imaging and image analysis are interdisciplinary areas combining electrical, computer, and biomedical engineering; computer science; mathem- ics; physics; statistics; biology; medicine; and other ?elds. Medical imaging and computer vision, interestingly enough, have developed and continue developing somewhat independently. Nevertheless, bringing them together promises to b- e?t both of these ?elds. We were enthusiastic when the organizers of the 2004 European Conference on Computer Vision (ECCV) allowed us to organize a satellite workshop devoted to medical image analysis.

Content-based Microscopic Image Analysis

Content-based Microscopic Image Analysis

by Chen Li

  • Publisher : Logos Verlag Berlin GmbH
  • Release : 2016-05-15
  • Pages : 196
  • ISBN : 3832542531
  • Language : En, Es, Fr & De
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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.

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

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

by Srivastava, Rajeev

  • Publisher : IGI Global
  • Release : 2013-09-30
  • Pages : 451
  • ISBN : 1466645598
  • Language : En, Es, Fr & De
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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.

Proceedings of International Conference on Computer Vision and Image Processing

Proceedings of International Conference on Computer Vision and Image Processing
CVIP 2016

by Balasubramanian Raman,Sanjeev Kumar,Partha Pratim Roy,Debashis Sen

  • Publisher : Springer
  • Release : 2016-12-22
  • Pages : 645
  • ISBN : 981102104X
  • Language : En, Es, Fr & De
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This edited volume contains technical contributions in the field of computer vision and image processing presented at the First International Conference on Computer Vision and Image Processing (CVIP 2016). The contributions are thematically divided based on their relation to operations at the lower, middle and higher levels of vision systems, and their applications. The technical contributions in the areas of sensors, acquisition, visualization and enhancement are classified as related to low-level operations. They discuss various modern topics – reconfigurable image system architecture, Scheimpflug camera calibration, real-time autofocusing, climate visualization, tone mapping, super-resolution and image resizing. The technical contributions in the areas of segmentation and retrieval are classified as related to mid-level operations. They discuss some state-of-the-art techniques – non-rigid image registration, iterative image partitioning, egocentric object detection and video shot boundary detection. The technical contributions in the areas of classification and retrieval are categorized as related to high-level operations. They discuss some state-of-the-art approaches – extreme learning machines, and target, gesture and action recognition. A non-regularized state preserving extreme learning machine is presented for natural scene classification. An algorithm for human action recognition through dynamic frame warping based on depth cues is given. Target recognition in night vision through convolutional neural network is also presented. Use of convolutional neural network in detecting static hand gesture is also discussed. Finally, the technical contributions in the areas of surveillance, coding and data security, and biometrics and document processing are considered as applications of computer vision and image processing. They discuss some contemporary applications. A few of them are a system for tackling blind curves, a quick reaction target acquisition and tracking system, an algorithm to detect for copy-move forgery based on circle block, a novel visual secret sharing scheme using affine cipher and image interleaving, a finger knuckle print recognition system based on wavelet and Gabor filtering, and a palmprint recognition based on minutiae quadruplets.

Computer Vision Approaches to Medical Image Analysis

Computer Vision Approaches to Medical Image Analysis
Second International ECCV Workshop, CVAMIA 2006, Graz, Austria, May 12, 2006, Revised Papers

by Reinhard R. Beichel,Milan Sonka

  • Publisher : Springer
  • Release : 2006-10-20
  • Pages : 264
  • ISBN : 3540462589
  • Language : En, Es, Fr & De
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This book constitutes the thoroughly refereed post proceedings of the international workshop Computer Vision Approaches to Medical Image Analysis, CVAMIA 2006, held in Graz, Austria in May 2006 as a satellite event of the 9th European Conference on Computer Vision, EECV 2006. The 10 revised full papers and 11 revised poster papers presented together with one invited talk were carefully reviewed and selected from 38 submissions.

A Study of Computer Vision and Pattern Recognition in Medical Image Analysis

A Study of Computer Vision and Pattern Recognition in Medical Image Analysis
Digital Microscopy and Optical Coherent Tomography

by Jun Kong

  • Publisher : Unknown Publisher
  • Release : 2008
  • Pages : 230
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Abstract: Computer vision and pattern recognition techniques have been fostered to solve many practical problems of diverse areas. Medical image analysis using machine vision and learning intelligence is one of the most sought-after fields. Computer vision addresses problems of the use of computers to detect, partition, represent, group, track, and interpret crucial primitives from given visual inputs. By contrast, pattern recognition is the study of distinguishing and recognizing different patterns represented with quantitative measurements. As a result, both of these two components usually present themselves in medical image analysis research work.

Applied Computer Vision and Image Processing

Applied Computer Vision and Image Processing
Proceedings of ICCET 2020, Volume 1

by Brijesh Iyer,A. M. Rajurkar,Venkat Gudivada

  • Publisher : Springer Nature
  • Release : 2020-08-29
  • Pages : 432
  • ISBN : 9811540292
  • Language : En, Es, Fr & De
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This book gathers high-quality research papers presented at the International Conference on Computing in Engineering and Technology (ICCET 2020) [formerly ICCASP]. A flagship conference on engineering and emerging next-generation technologies, it was jointly organized by Dr. Babasaheb Ambedkar Technological University and MGMs College of Engineering, Nanded, India on 9–11 January 2020. Focusing on applied computer vision and image processing, this proceedings volume includes papers on image processing, computer vision, pattern recognition, and DSP/DIP applications in healthcare systems.