Title Page	5
	Copyright Page	6
	Contents	7
	List of Contributors	13
	Foreword	15
	Chapter 1 Digital Microscopy: Nature to Numbers	17
	1.1 Acquisition	20
	1.1.1 First Principles: How Can Images Be Quantified?	20
	1.1.2 Representing Images as a Numerical Matrix Using a Scientific Camera	22
	1.1.3 Controlling Pixel Size in Cameras	24
	1.2 Initialisation	27
	1.2.1 The Sample	28
	1.2.2 Pre-Processing	28
	1.2.3 Denoising	28
	1.2.4 Filtering Images	30
	1.2.5 Deconvolution	32
	1.2.6 Registration and Calibration	35
	1.3 Measurement	37
	1.4 Interpretation	39
	1.5 References	45
	Chapter 2 Quantification of Image Data	47
	2.1 Making Sense of Images	47
	2.1.1 The Magritte Pipe	47
	2.1.2 Quantification of Image Data Via Computers	49
	2.2 Quantifiable Information	51
	2.2.1 Measuring and Comparing Intensities	51
	2.2.2 Quantifying Shape	52
	2.2.3 Spatial Arrangement of Objects	57
	2.3 Wrapping Up	61
	2.4 References	62
	Chapter 3 Segmentation in Bioimaging	63
	3.1 Segmentation and Information Condensation	63
	3.1.1 A Priori Knowledge	64
	3.1.2 An Intuitive Approach	65
	3.1.3 A Strategic Approach	67
	3.2 Extracting Objects	68
	3.2.1 Detecting and Counting Objects	68
	3.2.2 Automated Segmentation of Objects	76
	3.3 Wrapping Up	90
	3.4 References	95
	Chapter 4 Measuring Molecular Dynamics and Interactions by Förster Resonance Energy Transfer (FRET)	99
	4.1 FRET-based techniques	99
	4.1.1 Ratiometric Imaging	100
	4.1.2 Acceptor Photobleaching	101
	4.1.3 Other FRET Measurement Techniques	101
	4.1.4 Alternative Methods to Measure Interactions	103
	4.2 Experimental Design	105
	4.2.1 Ratiometric Imaging of FRET-Based Sensors	106
	4.2.2 Acceptor Photobleaching	107
	4.3 FRET Data Analysis	108
	4.3.1 Ratiometric Imaging	108
	4.3.2 Acceptor Photobleaching	109
	4.3.3 Data Averaging and Statistical Analysis	109
	4.4 Computational Aspects of Data Processing	110
	4.4.1 Software Tools	110
	4.4.2 FRET Data Analysis with Fiji	110
	4.5 Concluding Remarks	111
	4.6 References	112
	Chapter 5 FRAP and Other Photoperturbation Techniques	115
	5.1 Photoperturbation Techniques in Cell Biology	115
	5.1.1 Scientific Principles Underpinning FRAP	116
	5.1.2 Other Photoperturbation Techniques	119
	5.2 FRAP Experiments	122
	5.2.1 Selecting Fluorescent Tags	123
	5.2.2 Optimisation of FRAP Experiments	123
	5.2.3 Storage of Experimental Data	125
	5.3 FRAP Data Analysis	125
	5.3.1 Quantification of FRAP Intensities	128
	5.3.2 Normalisation	129
	5.3.3 In Silico Modelling of FRAP Data	131
	5.3.4 Fitting Recovery Curves	136
	5.3.5 Evaluating the Quality of FRAP Data and Analysis Results	137
	5.3.6 Data Averaging and Statistical Analysis	138
	5.3.7 Software for FRAP Data Processing	139
	5.4 Procedures for Quantitative FRAP Analysis with Freeware Software Tools	143
	5.4.1 Quantification of Intensity Traces with Fiji	143
	5.4.2 Processing FRAP Recovery Curves with FRAP Analyser	144
	5.5 Notes	146
	5.6 Concluding Remarks	147
	5.7?References	148
	5A Case Study: Analysing COPII Turnover During ER Exit	151
	5A.1 Quantitative FRAP Analysis of ER-Exit Sites	151
	5A.2 Mechanistic Insight into COPII Coat Kinetics with FRAP	154
	5A.3 Automated FRAP at ERESs	156
	5A.4 References	157
	Chapter 6 Co-Localisation and Correlation in Fluorescence Microscopy Data	159
	6.1 Introduction	159
	6.2 Co-Localisation for Conventional Microscopy Images	161
	6.2.1 Co-Localisation in Super-Resolution Localisation Microscopy	167
	6.2.2 Fluorescence Correlation Spectroscopy	172
	6.2.3 Image Correlation Spectroscopy	177
	6.3 Conclusion	180
	6.4 Acknowledgments	181
	6.5 References	181
	Chapter 7 Live Cell Imaging: Tracking Cell Movement	189
	7.1 Introduction	189
	7.2 Setting up a Movie for Time-Lapse Imaging	190
	7.3 Overview of Automated and Manual Cell Tracking Software	191
	7.3.1 Automatic Tracking	192
	7.3.2 Manual Tracking	196
	7.3.3 Comparison Between Automated and Manual Tracking	197
	7.4 Instructions for Using ImageJ Tracking	200
	7.5 Post-Tracking Analysis Using the Dunn Mathematica Software	205
	7.6 Summary and Future Direction	214
	7.7 References	214
	Chapter 8 Super-Resolution Data Analysis	217
	8.1 Introduction to Super-Resolution Microscopy	217
	8.2 Processing Structured Illumination Microscopy Data	218
	8.2.1 SIM Reconstruction Theory	219
	8.2.2 Parameter Fitting and Corrections	220
	8.2.3 SIM Quality Control	221
	8.2.4 Checking System Calibration	221
	8.2.5 Checking Raw Data	221
	8.2.6 Checking Reconstructed Data	224
	8.2.7 SIM Data Analysis	224
	8.3 Quantifying Single Molecule Localisation Microscopy Data	226
	8.3.1 SMLMS Pre-Processing	226
	8.3.2 Localisation: Finding Molecule Positions	226
	8.3.3 Fitting Molecules	226
	8.3.4 Problem of Multiple Emissions Per Molecule	228
	8.3.5 Sieving and Quality Control and Drift Correction	229
	8.3.6 How Far Can I Trust the SMLM Data?	234
	8.4 Reconstruction Summary	236
	8.5 Image Analysis on Localisation Data	236
	8.5.1 Cluster Analysis	237
	8.5.2 Stoichiometry and Counting	238
	8.5.3 Fitting and Particle Averaging	239
	8.5.4 Tracing	239
	8.6 Summary and Available Tools	239
	8.7 References	240
	Chapter 9 Big Data and Bio-Image Informatics: A Review of Software Technologies Available for Quantifying Large Datasets in Light-Microscopy	243
	9.1 Introduction	243
	9.2 What is Big Data Anyway?	244
	9.3 The Open-Source Bioimage Informatics Community	247
	9.3.1 ImageJ for Small-Scale Projects	247
	9.3.2 CellProfiler, Large-Scale Projects and the Need for Complex Infrastructure	251
	9.3.3 Technical Notes – Setting Up CellProfiler for Use on a Linux HPC	254
	9.3.4 Icy, Towards Reproducible Image Informatics	258
	9.4 Commercial Solutions for Bioimage Informatics	259
	9.4.1 Imaris Bitplane	259
	9.4.2 Definiens and Using Machine?Learning on Complex Datasets	260
	9.5 Summary	263
	9.6 Acknowledgments	263
	9.7 References	264
	Chapter 10 Presenting and storing data for publication	265
	10.1 How to Make Scientific Figures	265
	10.1.1 General Guidelines for Making Any Microscopy Figure	266
	10.1.2 Do’s and Don’ts: Preparation of Figures for Publication	267
	10.1.3 Restoration, Revelation or Manipulation	269
	10.2 Presenting, Documenting and Storing Bioimage Data	272
	10.2.1 Metadata Matters	273
	10.2.2 The Open Microscopy Project	274
	10.2.3 OME and Bio-Formats, Supporting Interoperability in Bioimaging Data	275
	10.2.4 Long-Term Data Storage	276
	10.2.5 USB Drives Friend or Foe?	278
	10.2.6 Beyond the (USB) Drive Limit	278
	10.2.7 Servers and Storage Area Networks	279
	10.2.8 OMERO Scalable Data Management for Biologists	281
	10.3 Summary	283
	10.4 References	284
	Chapter 11 Epilogue: A Framework for Bioimage Analysis	285
	11.1 Workflows for Bioimage Analysis	286
	11.1.1 Components	286
	11.1.2 Workflows	288
	11.1.3 Types of Workflows	289
	11.1.4 Types of Component	292
	11.2 Resources for Designing Workflows and Supporting Bioimage Analysis	293
	11.2.1 A Brief History	294
	11.2.2 A Network for Bioimage Analysis	295
	11.2.3 Additional Textbooks	295
	11.2.4 Training Schools	296
	11.2.5 Database of Components and Workflows	296
	11.2.6 Benchmarking Platform	298
	11.3 Conclusion	298
	11.4 References	299
	Index	301
	EULA	310