Web microanalysis of big image data /
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Author / Creator: | Bajcsy, Peter, author. |
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Imprint: | Cham : Springer, [2018] ©2018 |
Description: | 1 online resource : illustrations (some color) |
Language: | English |
Subject: | Big data. Image processing -- Digital techniques. COMPUTERS -- Image Processing. Pattern recognition. Applied mathematics. Imaging systems & technology. Big data. Image processing -- Digital techniques. Electronic books. |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11544134 |
Table of Contents:
- Intro; Preface; Terminology; Acknowledgments; Disclaimer; Abbreviations; Contents; Chapter 1: Introduction to Big Data Microscopy Experiments; 1.1 Image Processing Pipeline; 1.2 Web Image Processing Pipeline; 1.3 Big Data Microscopy Experiments; 1.4 Motivation of Big Data Microscopy Experiments; 1.5 Range of Applications Leveraging Image Processing Pipelines; 1.6 Challenges of Big Data Microscopy Experiments; 1.7 Considerations Before and After Digital Images Are Acquired; 1.8 Enabling Reproducible Science from Big Data Microscopy Experiments; References.
- Chapter 2: Functionality of Web Image Processing Pipeline2.1 Deploying and Testing the Web Image Processing Pipeline; 2.1.1 Types of Deployment; 2.1.2 Deployment of Docker Containers; 2.1.3 Deployment Recommendations; 2.1.4 Test Data and Computational Benchmarks; 2.2 Web Image Processing Module; 2.2.1 Web Image Processing Module Processing Functionality; 2.2.2 Description of WIP Module Usage; 2.3 Web Feature Extraction Module; 2.3.1 WFE Module Processing Functionality; 2.3.2 WFE Module Usage; 2.4 Web Statistical Modeling Module; 2.4.1 WSM Module Processing Functionality.
- 2.4.2 WSM Module Usage2.5 Summary; References; Chapter 3: Example Use Cases; 3.1 Cell Count and Single Cell Detection; 3.1.1 Image Processing Workflow; 3.1.2 Create a New Image Collection; 3.1.3 Stitching of Image Tiles; 3.1.4 Intensity Scaling and Pyramid Building; 3.1.5 Image Assembling; 3.1.6 Segmentation; 3.1.7 Binary Image Labeling; 3.1.8 Feature Extraction and Single Cell Detection; 3.1.9 Discussion; 3.2 Stem Cell Colony Growth Computation; 3.2.1 Image Processing Workflow; 3.2.2 Colony Tracking and Feature Extraction; 3.2.3 Discussion; 3.3 Image Feature Variability and Its Impact.
- 3.3.1 Image Processing Workflow3.3.2 Image Feature Variability Analysis; 3.3.3 Discussion; 3.4 Summary; References; Chapter 4: Components of Web Image Processing Pipeline; 4.1 Mapping Functionality to Information Technologies; 4.2 The Basics of Client-Server Architecture; 4.2.1 The Role of Each Technology in the Client-Server Architecture; 4.3 The Basics of Web Servers and Browsers; 4.4 The Basics of Communication Protocols in Client-Server Architectures; 4.4.1 Client-Server Communication Using Hypertext Transfer Protocol; 4.4.2 Transmission Control Protocol (TCP).
- 4.4.3 Message Passing Interface4.4.4 Network File System; 4.5 Designing Interactive User Interfaces in Web Browsers; 4.5.1 Model-View-Controller Design Pattern; 4.5.2 AngularJS for Building Interactive User Interfaces; 4.6 Large Image Visualization and Processing in Web Browsers; 4.7 Representation of Large Images; 4.7.1 Large Image Visualization in Web Browsers; 4.7.2 Image Processing in Web Browsers; 4.8 Managing Images, Pyramids, and Metadata; 4.8.1 Relational Databases; 4.8.2 Non-relational Database; 4.8.3 Java Spring Framework for Web Application Development.