Computer Vision for Microscopy Image Analysis

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  • Publisher : Academic Press
  • Release : 01 December 2020
  • ISBN : 9780128149737
  • Page : 230 pages
  • Rating : 4.5/5 from 103 voters

Computer Vision for Microscopy Image Analysis Book PDF 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

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Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
  • Author : Mei Chen
  • Publisher : Academic Press
  • Release Date : 2020-12-01
  • ISBN : 9780128149737
DOWNLOAD BOOKComputer 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

Microscope Image Processing

Microscope Image Processing
  • Author : Qiang Wu,Fatima Merchant,Kenneth Castleman
  • Publisher : Elsevier
  • Release Date : 2010-07-27
  • ISBN : 0080558542
DOWNLOAD BOOKMicroscope 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

Computer Vision and Machine Learning for Microscopy Image Analysis

Computer Vision and Machine Learning for Microscopy Image Analysis
  • Author : Carlos Federico Arteta
  • Publisher : Unknown
  • Release Date : 2015
  • ISBN : OCLC:1065077482
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Content-based Microscopic Image Analysis

Content-based Microscopic Image Analysis
  • Author : Chen Li
  • Publisher : Logos Verlag Berlin GmbH
  • Release Date : 2016-05-15
  • ISBN : 9783832542535
DOWNLOAD BOOKContent-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)

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
  • Publisher : Springer
  • Release Date : 2019-03-02
  • ISBN : 9783030134693
DOWNLOAD BOOKProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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

Image Technology

Image Technology
  • Author : Jorge L.C. Sanz
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • ISBN : 9783642582882
DOWNLOAD BOOKImage 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.

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 Date : 2008
  • ISBN : 9781596932371
DOWNLOAD BOOKMicroscopic 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.

Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
  • Author : S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
  • Publisher : Academic Press
  • Release Date : 2017-01-18
  • ISBN : 9780128104095
DOWNLOAD BOOKDeep 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