Modern Trends in Diatom Identification: Fundamentals and Applications

Foreword
	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
Index