-.

Identification of Diatoms: From Subjectivity to Objectivity Species Identification Discrete and Continuous Variables Recognition, Identification, Classification From Subjectivity to Objectivity References Preface Acknowledgements Contents Contributors Part I Fundamentals 1 Overview: Antecedents, Motivation and Necessity 1.1 Introduction 1.2 Organization of the Book Chapters 1.3 Other Diatom-Related Resources 1.3.1 Databases and Software 1.3.2 Journals and Reference Books 1.3.3 Conferences/Societies 1.3.4 Research Projects 1.3.5 Diatom Collections/Catalogs 1.4 Diatom Drawings 1.5 Social Impact/Educational Projects 1.6 Conclusions References 2 Diatom Classifications: What Purpose Do They Serve? 2.1 Introduction 2.2 Diatoms 2.3 Scientific Classification 2.4 Diatoms: Classification and Identification 2.5 Artificial Diatom Classifications 2.5.1 Three Randomly Selected Identification Guides 2.5.2 Three Non-Randomly Selected Identification Guides 2.6 Natural Diatom Classifications 2.6.1 Two Non-randomly Selected “Natural” Classifications 2.7 Automatic Identification 2.8 Numbers of Species 2.8.1 What Do We (Think We) Know? 2.8.2 What Would We Like to Know? 2.8.3 What Do We Know? 2.9 Specimens 2.10 Conclusions References 3 Diatom Taxonomy and Identification Keys 3.1 The Value of Taxonomic Keys for Applied Diatomology 3.2 Overview on Diatom Morphology 3.3 Diatom Illustrations: From Drawings to Electron Microscopy 3.4 Conclusions A.1 Annex A.1.1 Quick Guide to Common Diatom Genera in Freshwaters References 4 Naturally and Environmentally Driven Variations in Diatom Morphology: Implications for Diatom-Based Assessment of Water Quality 4.1 Teratology in Algae, with a Special Focus on Diatoms 4.2 The Effect of Overriding Diatom Teratology on Water Quality Diagnosis 4.3 Intra- and Interpopulational Variations in Diatom Frustule Size and Shape 4.4 The Sample Size of Type Populations: Implications for Taxonomic Diagnoses 4.5 Conclusions References Part II Sensing 5 Microscopic Modalities and Illumination Techniques 5.1 Introduction 5.2 Principles and Optical Basics in Light Microscopy 5.2.1 Light Pathway of a Compound Microscope 5.2.2 Optical Components in General 5.2.2.1 Light Source 5.2.2.2 Condenser 5.2.2.3 Objective 5.2.2.4 Tube Lens 5.2.2.5 Eyepiece 5.3 Standard Illumination Techniques 5.3.1 Bright-Field 5.3.2 Eccentric Oblique Bright-Field 5.3.3 Concentric Oblique Bright-Field (Circular Oblique Lighting) 5.3.4 Dark-Field 5.3.4.1 Dark-Field Based on Peripheral Light 5.3.4.2 Dark-Field Based on Central Light 5.3.5 Rheinberg Illumination 5.3.6 Phase Contrast 5.3.7 Polarized Light Microscopy 5.3.8 Differential Interference Contrast 5.3.9 Fluorescence Microscopy 5.3.10 Incident Light Microscopy (Epi-illumination) 5.4 Modifications of Standard Illumination Techniques and Variable Multimodal Techniques 5.4.1 Apodized Phase Contrast 5.4.2 Relief Phase Contrast 5.4.3 Aperture Reduction Phase Contrast 5.4.4 Aperture Reduction Dark-Field 5.4.5 Digital Dark-Field 5.4.6 Digital Phase Contrast 5.4.7 Luminance Contrast 5.4.8 Fluorescence Luminance Contrast 5.4.9 Variable Bright-Dark-Field Contrast 5.4.10 Variable Phase-Dark-Field Contrast 5.4.11 Axial Phase-Dark-Field Contrast 5.4.12 Variable Phase-Bright-Field Contrast 5.4.13 Variable Combinations of DIC with Phase Contrast and Dark-Field 5.4.13.1 Variable Interference-Phase Contrast 5.4.13.2 Variable Interference-Dark-Field Contrast 5.5 Conclusions References 6 Light Filtering in Microscopy 6.1 Introduction 6.2 Neutral Colorless Filters 6.2.1 UV–IR Cutters 6.2.2 Diffusers 6.2.3 Neutral Gray and Double Polarizing Filters 6.3 Color Modulating Filters 6.3.1 Blue “Daylight” Filters 6.3.2 Green Filters 6.3.3 Warming Filters for Blue LEDs 6.3.4 “Vario-Color” and “Pol-Color” Polarizing Filters 6.3.5 Monochromatic Interference Filters 6.3.6 RGB Filter Sets (Three-Shot Techniques) 6.3.7 RGB-Intensifying Filters 6.4 LED Versus Halogen (Bulb) Light 6.5 Conclusions References 7 Automatization Techniques. Slide Scanning 7.1 Introduction 7.2 Materials and Methods 7.2.1 Optical and Mechanical Performance 7.3 Programmable Illumination 7.3.1 Light Intensity Control 7.3.2 Programmable Illumination Modes 7.4 Image Calibration 7.4.1 Usage with ImageJ 7.5 Slide Scanning 7.5.1 Platform Motorization 7.5.2 Automatic Slide Scanning 7.5.2.1 Sequential Scanning 7.5.2.2 Random Scanning 7.5.2.3 Scanning Based on Regions of Interest 7.5.3 Autofocusing 7.5.3.1 Criteria to Measure the Focus Level 7.5.3.2 Autofocus Strategies 7.6 Preprocessing 7.6.1 Noise Reduction 7.6.2 Background Correction 7.6.2.1 Division by Blank Image 7.6.2.2 Division by Unfocused Image 7.6.2.3 Division by Polynomial Approximated Image 7.6.2.4 Division by Rolling Ball Background Image 7.6.2.5 Usage with ImageJ 7.6.2.6 Batch Processing 7.6.3 Contrast Enhancement 7.7 Conclusions Appendix Microscope Control Application General Configuration Stage Control Scanning and Processing Functions References Part III Analysis 8 Segmentation Techniques 8.1 Introduction 8.2 Classical Methods 8.2.1 Region- and Contour-Based Methods 8.2.1.1 Thresholding 8.2.1.2 Gradient-Based Methods 8.2.1.3 Deformable Models 8.2.2 Featured Based on Methods 8.2.2.1 Phase Congruency 8.2.2.2 Scale and Curvature Invariant 8.2.2.3 Viola–Jones 8.3 Deep Learning Techniques 8.3.1 Neural Networks 8.3.2 Convolutional Neural Networks 8.3.2.1 CNN Components 8.3.3 R-CNN 8.3.3.1 Post-processing 8.3.4 You Only Look Once 8.3.5 Semantic Segmentation 8.3.6 Instance Segmentation 8.4 Conclusions References 9 Diatom Feature Extraction and Classification 9.1 Introduction 9.2 Classification Using Machine Learning Hand-Crafted Techniques 9.2.1 Feature Extraction 9.2.1.1 Morphological Descriptors 9.2.1.2 Statistical Descriptors 9.2.1.3 Local Binary Patterns 9.2.1.4 Hu Moments 9.2.1.5 Log Gabor Transform 9.2.1.6 Elliptical Fourier Descriptors 9.2.1.7 Phase Congruency Descriptors 9.2.2 Feature Discriminant Analysis and Dimensionality Reduction 9.2.2.1 Correlation-Based Feature Selection 9.2.2.2 Sequential Forward Feature Selection 9.2.2.3 Principal Component Analysis (PCA) 9.2.2.4 Linear Discriminant Analysis (LDA) 9.2.3 Classifiers 9.2.3.1 Supervised Classifiers 9.2.3.2 Unsupervised Classifiers 9.2.4 Classification Performance 9.3 Classification Using Deep Learning Techniques 9.3.1 Learning Process 9.3.2 Parameters 9.3.3 Insights Visualization 9.4 Diatom Classification Results 9.5 Conclusions Appendix References 10 Multifocus and Multiexposure Techniques 10.1 Introduction 10.2 Multifocus Fusion Methods 10.2.1 Two-Scale Decomposition (TSD) 10.2.2 Detection of a Focused Region and Weight Map Computation 10.2.3 Weight Map Refinement 10.2.4 Weighted Average Fusion of BL and DL 10.3 Exposure Fusion (EF) vs High Dynamic Range (HDR) 10.3.1 HDR and Tone-Mapping 10.3.2 Exposure Fusion 10.4 Depth Map and 3-D Surface Visualization of Fusion Results 10.5 Fusion Quality Metrics 10.5.1 Gradient-Based Fusion Performance (QAB/F) 10.5.2 Image Fusion Metric Based on Spatial Frequency (QSF) 10.5.3 Average Gradient-Based Fusion Metric (QAG) 10.5.4 Entropy-Based Fusion Metric (QH) 10.6 Efficient Implementations 10.7 Discussion and Conclusions References 11 Stereoscopic Imaging of Diatoms in Light and Electron Microscopy 11.1 Introduction 11.1.1 Stereoscopy: Basic Concepts and Brief History 11.1.2 Physical Principles of Stereoscopy 11.1.3 Types of Stereo Images and Viewing Techniques 11.2 Three-Dimensional Imaging in LM 11.2.1 Basic Visualization Techniques 11.2.2 Stereoscopic LM Images of Diatoms 11.3 Three-Dimensional Imaging in EM 11.3.1 Basic Visualization Techniques 11.3.2 Stereoscopic SEM Images of Diatoms 11.4 Conclusion: Role of 3D Imaging in Diatom Research A.1 Appendix References 12 Geometric Morphometrics and the Shape of Microscopic Organisms 12.1 Introduction 12.2 Theory of Shape and Morphospaces 12.3 Geometric Morphometrics' Tools 12.3.1 Landmark-Based Methods 12.3.2 Outline-Based Methods 12.3.3 Eigenshape Analysis 12.3.4 Legendre Polynomials (Orthogonal Polynomial Regression) 12.4 Image Acquisition 12.5 Visualization of Shape Variation 12.5.1 Landmark-Based Methods 12.5.2 Outline-Based Methods 12.6 Quantification of Shape Variation 12.7 What Information Conveys the Analysis of Microscopic Imagery? 12.8 Conclusions Appendix: Software Available References Part IV Applications 13 Water Quality Assessment 13.1 Introduction 13.2 Sampling and Analytical Protocols 13.2.1 EU Standards 13.2.2 Automatic Diatom Identification 13.2.3 Diatom DNA Metabarcoding 13.3 Distribution and Frequency of Diatoms in the Iberian Peninsula 13.3.1 River Typologies: Siliceous and Calcareous 13.3.2 Reference Conditions 13.4 Diatom-Based Bioassessment Tools 13.4.1 European Autoecological Indexes: SPI, TDI, Rott, and ICM (Intercalibration Common Metric) 13.4.1.1 SPI (Specific Pollution Sensitivity Index) 13.4.1.2 TDI (Trophic Diatom Index) 13.4.1.3 Rott's Index 13.4.1.4 ICM (Intercalibration Common Metric) 13.4.2 Diatom Indexes Developed for the Iberian Peninsula 13.4.2.1 Multimetric Index: MDIAT 13.4.2.2 Autoecological Index: DDI 13.4.2.3 Ecological Distance Index: iDIAT-ES 13.4.3 Complementary Metrics Based on Diatoms (Growth Forms, Ecological Guilds, Teratologies) 13.5 ID-TAX: Identification Key for Biological Quality Elements Used in Routine Biological Monitoring in Spain 13.6 Conclusions References 14 Diatoms in Forensic Analysis 14.1 Introduction 14.1.1 Diatom Test in Drowning 14.1.2 Other Applications of Diatoms 14.1.2.1 Drowning Site 14.1.2.2 Suspects 14.1.2.3 Time of Death 14.2 Sample Preparation: A Review of Techniques for Diatom Analysis in Forensics 14.2.1 Acid Digestion Method 14.2.2 Acid Digestion in Disorganization Can 14.2.3 Soluene-350 Method 14.2.4 Enzymatic Digestion 14.2.5 Membrane Filter 14.2.6 Novel Techniques 14.2.7 Suspect Identification Methods 14.2.8 Evaluation of Methods for Extracting Diatoms in Tissues 14.3 Diatom Analysis 14.3.1 Diatom Identification 14.3.2 Water Analysis 14.3.2.1 Protocols 14.4 Histological Findings in Drowning 14.4.1 Skin Histological Findings 14.4.2 Lung Histological Findings 14.4.3 Muscle Histological Findings 14.5 Discussion and Conclusions 14.5.1 Main Controversies of Diatom Test 14.5.1.1 False Positives 14.5.1.2 False Negatives 14.5.2 Quantitative and Qualitative Analysis 14.5.2.1 Quantitative Analysis 14.5.2.2 Qualitative Analysis 14.5.3 Conclusions References 15 Benthic Foraminifera and Diatoms as Ecological Indicators 15.1 Introduction to Benthic Foraminifera and Diatoms: Basic Aspects of Biology and Ecology 15.2 Sampling and Foraminifera Analysis 15.3 Benthic Foraminifera and Diatoms as Modern and Past Ecological Indicators 15.4 Multiproxy Analysis 15.5 Conclusions and Implications Illustration Plates of Foraminifera Glossary