Computer Vision for Microscopy Image Analysis

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

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  • Author : Mei Chen, Ph.D
  • Publisher : Academic Press
  • Pages : 350 pages
  • ISBN : 9780128149720
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKComputer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
  • Author : Mei Chen, Ph.D
  • Publisher : Academic Press
  • Release : 15 February 2019
GET THIS BOOKComputer Vision for Microscopy Image Analysis

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

Computer Vision for Microscopy Image Analysis

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

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 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

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 : 20 May 2022
GET THIS 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.

Computer Vision for Electronics Manufacturing

Computer Vision for Electronics Manufacturing
  • Author : L.F Pau
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKComputer Vision for Electronics Manufacturing

DEFECT PROPORTION OF DETECTION INITIAL RATE DETECTION RATE INSPECTOR 3 COMPLEXITY OF TIMES PAN OF PERFORMING o~ ________________________ o~ ______________________ __ -;. INSPECTION TASK -;. VISUAL INSPECTION Fagure 1. Trends in relations between the complexity of inspection tasks, defect detection rates (absolute and relative), and inspection time. Irrespective of the necessities described above, and with the excep tion of specific generic application systems (e.g., bare-board PCB inspection, wafer inspection, solder joint inspection, linewidth measure ment), vision systems are still not found frequently in today's

Decision Forests for Computer Vision and Medical Image Analysis

Decision Forests for Computer Vision and Medical Image Analysis
  • Author : Antonio Criminisi,J Shotton
  • Publisher : Springer Science & Business Media
  • Release : 30 January 2013
GET THIS BOOKDecision Forests for Computer Vision and Medical Image Analysis

This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision

Microscope Image Processing

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

Group and Crowd Behavior for Computer Vision

Group and Crowd Behavior for Computer Vision
  • Author : Vittorio Murino,Marco Cristani,Shishir Shah,Silvio Savarese
  • Publisher : Academic Press
  • Release : 18 April 2017
GET THIS BOOKGroup and Crowd Behavior for Computer Vision

Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis
  • Author : Nilanjan Dey
  • Publisher : Academic Press
  • Release : 31 July 2019
GET THIS BOOKClassification Techniques for Medical Image Analysis and Computer Aided Diagnosis

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep

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

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
  • Author : João Manuel R. S. Tavares,João Paulo Papa,Manuel González Hidalgo
  • Publisher : Springer Nature
  • Release : 13 January 2022
GET THIS BOOKProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

This book constitutes the proceedings of the 25th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2021, which took place during May 10–13, 2021. The conference was initially planned to take place in Porto, Portugal, but changed to a virtual event due to the COVID-19 pandemic. The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They were organized in topical sections as follows: medical applications; natural language processing; metaheuristics; image segmentation; databases; deep

Data Science for Nano Image Analysis

Data Science for Nano Image Analysis
  • Author : Chiwoo Park,Yu Ding
  • Publisher : Springer Nature
  • Release : 31 July 2021
GET THIS BOOKData Science for Nano Image Analysis

This book combines two distinctive topics: data science/image analysis and materials science. The purpose of this book is to show what type of nano material problems can be better solved by which set of data science methods. The majority of material science research is thus far carried out by domain-specific experts in material engineering, chemistry/chemical engineering, and mechanical & aerospace engineering. The book could benefit materials scientists and manufacturing engineers who were not exposed to systematic data science training

Content-based Microscopic Image Analysis

Content-based Microscopic Image Analysis
  • Author : Chen Li
  • Publisher : Logos Verlag Berlin GmbH
  • Release : 15 May 2016
GET THIS 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 : José Ruiz-Shulcloper,Gabriella Sanniti di Baja
  • Publisher : Springer
  • Release : 04 November 2013
GET THIS BOOKProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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.

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 BOOKProgress 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.