{"product_id":"imaging-life-9781119949206","title":"Imaging Life","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eImaging Life is an accessible textbook that covers scientific imaging, from creating pictures with a wide range of instruments, to processing and analyzing them.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xii\u003c\/p\u003e \u003cp\u003eAcknowledgments xiv\u003c\/p\u003e \u003cp\u003eAbout the Companion Website xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 1 Image Acquisition 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Image Structure and Pixels 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 The Pixel Is the Smallest Discrete Unit of a Picture 3\u003c\/p\u003e \u003cp\u003e1.2 The Resolving Power of a Camera or Display Is the Spatial Frequency of Its Pixels 6\u003c\/p\u003e \u003cp\u003e1.3 Image Legibility Is the Ability to Recognize Text in an Image by Eye 7\u003c\/p\u003e \u003cp\u003e1.4 Magnification Reduces Spatial Frequencies While Making Bigger Images 9\u003c\/p\u003e \u003cp\u003e1.5 Technology Determines Scale and Resolution 11\u003c\/p\u003e \u003cp\u003e1.6 The Nyquist Criterion: Capture at Twice the Spatial Frequency of the Smallest Object Imaged 12\u003c\/p\u003e \u003cp\u003e1.7 Archival Time, Storage Limits, and the Resolution of the Display Medium Influence Capture and Scan Resolving Power 13\u003c\/p\u003e \u003cp\u003e1.8 Digital Image Resizing or Scaling Match the Captured Image Resolution to the Output Resolution 14\u003c\/p\u003e \u003cp\u003e1.9 Metadata Describes Image Content, Structure, and Conditions of Acquisition 16\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Pixel Values and Image Contrast 20\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Contrast Compares the Intensity of a Pixel with That of Its Surround 20\u003c\/p\u003e \u003cp\u003e2.2 Pixel Values Determine Brightness and Color 21\u003c\/p\u003e \u003cp\u003e2.3 The Histogram Is a Plot of the Number of Pixels in an Image at Each Level of Intensity 24\u003c\/p\u003e \u003cp\u003e2.4 Tonal Range Is How Much of the Pixel Depth Is Used in an Image 25\u003c\/p\u003e \u003cp\u003e2.5 The Image Histogram Shows Overexposure and Underexposure 26\u003c\/p\u003e \u003cp\u003e2.6 High-Key Images Are Very Light, and Low-Key Images Are Very Dark 27\u003c\/p\u003e \u003cp\u003e2.7 Color Images Have Various Pixel Depths 27\u003c\/p\u003e \u003cp\u003e2.8 Contrast Analysis and Adjustment Using Histograms Are Available in Proprietary and Open-Source Software 29\u003c\/p\u003e \u003cp\u003e2.9 The Intensity Transfer Graph Shows Adjustments of Contrast and Brightness Using Input and Output Histograms 30\u003c\/p\u003e \u003cp\u003e2.10 Histogram Stretching Can Improve the Contrast and Tonal Range of the Image without Losing Information 32\u003c\/p\u003e \u003cp\u003e2.11 Histogram Stretching of Color Channels Improves Color Balance 32\u003c\/p\u003e \u003cp\u003e2.12 Software Tools for Contrast Manipulation Provide Linear, Non-linear, and Output-Visualized Adjustment 34\u003c\/p\u003e \u003cp\u003e2.13 Different Image Formats Support Different Image Modes 36\u003c\/p\u003e \u003cp\u003e2.14 Lossless Compression Preserves Pixel Values, and Lossy Compression Changes Them 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Representation and Evaluation of Image Data 42\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Image Representation Incorporates Multiple Visual Elements to Tell a Story 42\u003c\/p\u003e \u003cp\u003e3.2 Illustrated Confections Combine the Accuracy of a Typical Specimen with a Science Story 42\u003c\/p\u003e \u003cp\u003e3.3 Digital Confections Combine the Accuracy of Photography with a Science Story 45\u003c\/p\u003e \u003cp\u003e3.4 The Video Storyboard Is an Explicit Visual Confection 48\u003c\/p\u003e \u003cp\u003e3.5 Artificial Intelligence Can Generate Photorealistic Images from Text Stories 48\u003c\/p\u003e \u003cp\u003e3.6 Making Images Believable: Show Representative Images and State the Acquisition Method 50\u003c\/p\u003e \u003cp\u003e3.7 Making Images Understood: Clearly Identify Regions of Interest with Suitable Framing, Labels, and Image Contrast 51\u003c\/p\u003e \u003cp\u003e3.8 Avoid Dequantification and Technical Artifacts While Not Hesitating to Take the Picture 55\u003c\/p\u003e \u003cp\u003e3.9 Accurate, Reproducible Imaging Requires a Set of Rules and Guidelines 56\u003c\/p\u003e \u003cp\u003e3.10 The Structural Similarity Index Measure Quantifies Image Degradation 57\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Image Capture by Eye 61\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The Anatomy of the Eye Limits Its Spatial Resolution 61\u003c\/p\u003e \u003cp\u003e4.2 The Dynamic Range of the Eye Exceeds 11 Orders of Magnitude of Light Intensity, and Intrascene Dynamic Range Is about 3 Orders 63\u003c\/p\u003e \u003cp\u003e4.3 The Absorption Characteristics of Photopigments of the Eye Determines Its Wavelength Sensitivity 63\u003c\/p\u003e \u003cp\u003e4.4 Refraction and Reflection Determine the Optical Properties of Materials 67\u003c\/p\u003e \u003cp\u003e4.5 Movement of Light Through the Eye Depends on the Refractive Index and Thickness of the Lens, the Vitreous Humor, and Other Components 69\u003c\/p\u003e \u003cp\u003e4.6 Neural Feedback in the Brain Dictates Temporal Resolution of the Eye 69\u003c\/p\u003e \u003cp\u003e4.7 We Sense Size and Distribution in Large Spaces Using the Rules of Perspective 70\u003c\/p\u003e \u003cp\u003e4.8 Three-Dimensional Representation Depends on Eye Focus from Different Angles 71\u003c\/p\u003e \u003cp\u003e4.9 Binocular Vision Relaxes the Eye and Provides a Three-Dimensional View in Stereomicroscopes 74\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Image Capture with Digital Cameras 78\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Digital Cameras are Everywhere 78\u003c\/p\u003e \u003cp\u003e5.2 Light Interacts with Silicon Chips to Produce Electrons 78\u003c\/p\u003e \u003cp\u003e5.3 The Anatomy of the Camera Chip Limits Its Spatial Resolution 80\u003c\/p\u003e \u003cp\u003e5.4 Camera Chips Convert Spatial Frequencies to Temporal Frequencies with a Series of Horizontal and Vertical Clocks 82\u003c\/p\u003e \u003cp\u003e5.5 Different Charge-Coupled Device Architectures Have Different Read-out Mechanisms 85\u003c\/p\u003e \u003cp\u003e5.6 The Digital Camera Image Starts Out as an Analog Signal that Becomes Digital 87\u003c\/p\u003e \u003cp\u003e5.7 Video Broadcast Uses Legacy Frequency Standards 88\u003c\/p\u003e \u003cp\u003e5.8 Codecs Code and Decode Digital Video 89\u003c\/p\u003e \u003cp\u003e5.9 Digital Video Playback Formats Vary Widely, Reflecting Different Means of Transmission and Display 91\u003c\/p\u003e \u003cp\u003e5.10 The Light Absorption Characteristics of the Metal Oxide Semiconductor, Its Filters, and Its Coatings Determine the Wavelength Sensitivity of the Camera Chip 91\u003c\/p\u003e \u003cp\u003e5.11 Camera Noise and Potential Well Size Determine the Sensitivity of the Camera to Detectable Light 93\u003c\/p\u003e \u003cp\u003e5.12 Scientific Camera Chips Increase Light Sensitivity and Amplify the Signal 97\u003c\/p\u003e \u003cp\u003e5.13 Cameras for Electron Microscopy Use Regular Imaging Chips after Converting Electrons to Photons or Detect the Electron Signal Directly with Modified CMOS 99\u003c\/p\u003e \u003cp\u003e5.14 Camera Lenses Place Additional Constraints on Spatial Resolution 101\u003c\/p\u003e \u003cp\u003e5.15 Lens Aperture Controls Resolution, the Amount of Light, the Contrast, and the Depth of Field in a Digital Camera 106\u003c\/p\u003e \u003cp\u003e5.16 Relative Magnification with a Photographic Lens Depends on Chip Size and Lens Focal Length 107\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Image Capture by Scanning Systems 111\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Scanners Build Images Point by Point, Line by Line, and Slice by Slice 111\u003c\/p\u003e \u003cp\u003e6.2 Consumer-Grade Flatbed Scanners Provide Calibrated Color and Relatively High Resolution Over a Wide Field of View 111\u003c\/p\u003e \u003cp\u003e6.3 Scientific-Grade Flatbed Scanners Can Detect Chemiluminescence, Fluorescence, and Phosphorescence 114\u003c\/p\u003e \u003cp\u003e6.4 Scientific-Grade Scanning Systems Often Use Photomultiplier Tubes and Avalanche Photodiodes as the Camera 118\u003c\/p\u003e \u003cp\u003e6.5 X-ray Planar Radiography Uses Both Scanning and Camera Technologies 119\u003c\/p\u003e \u003cp\u003e6.6 Medical Computed Tomography Scans Rotate the X-ray Source and Sensor in a Helical Fashion Around the Body 121\u003c\/p\u003e \u003cp\u003e6.7 Micro-CT and Nano-CT Scanners Use Both Hard and Soft X-Rays and Can Resolve Cellular Features 123\u003c\/p\u003e \u003cp\u003e6.8 Macro Laser Scanners Acquire Three-Dimensional Images by Time-of-Flight or Structured Light 125\u003c\/p\u003e \u003cp\u003e6.9 Laser Scanning and Spinning Disks Generate Images for Confocal Scanning Microscopy 126\u003c\/p\u003e \u003cp\u003e6.10 Electron Beam Scanning Generates Images for Scanning Electron Microscopy 128\u003c\/p\u003e \u003cp\u003e6.11 Atomic Force Microscopy Scans a Force-Sensing Probe Across the Sample 128\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 2 Image Analysis 135\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Measuring Selected Image Features 137\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Digital Image Processing and Measurements are Part of the Image Metadata 137\u003c\/p\u003e \u003cp\u003e7.2 The Subject Matter Determines the Choice of Image Analysis and Measurement Software 140\u003c\/p\u003e \u003cp\u003e7.3 Recorded Paths, Regions of Interest, or Masks Save Selections for Measurement in Separate Images, Channels, and Overlays 140\u003c\/p\u003e \u003cp\u003e7.4 Stereology and Photoquadrat Sampling Measure Unsegmented Images 144\u003c\/p\u003e \u003cp\u003e7.5 Automatic Segmentation of Images Selects Image Features for Measurement Based on Common Feature Properties 146\u003c\/p\u003e \u003cp\u003e7.6 Segmenting by Pixel Intensity Is Thresholding 146\u003c\/p\u003e \u003cp\u003e7.7 Color Segmentation Looks for Similarities in a Three-Dimensional Color Space 147\u003c\/p\u003e \u003cp\u003e7.8 Morphological Image Processing Separates or Connects Features 149\u003c\/p\u003e \u003cp\u003e7.9 Measures of Pixel Intensity Quantify Light Absorption by and Emission from the Sample 153\u003c\/p\u003e \u003cp\u003e7.10 Morphometric Measurements Quantify the Geometric Properties of Selections 155\u003c\/p\u003e \u003cp\u003e7.11 Multi-dimensional Measurements Require Specific Filters 156\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Optics and Image Formation 161\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Optical Mechanics Can Be Well Described Mathematically 161\u003c\/p\u003e \u003cp\u003e8.2 A Lens Divides Space Into Image and Object Spaces 161\u003c\/p\u003e \u003cp\u003e8.3 The Lens Aperture Determines How Well the Lens Collects Radiation 163\u003c\/p\u003e \u003cp\u003e8.4 The Diffraction Limit and the Contrast between Two Closely Spaced Self-Luminous Spots Give Rise to the Limits of Resolution 164\u003c\/p\u003e \u003cp\u003e8.5 The Depth of the Three-Dimensional Slice of Object Space Remaining in Focus Is the Depth of Field 167\u003c\/p\u003e \u003cp\u003e8.6 In Electromagnetic Lenses, Focal Length Produces Focus and Magnification 170\u003c\/p\u003e \u003cp\u003e8.7 The Axial, Z-Dimensional, Point Spread Function Is a Measure of the Axial Resolution of High Numerical Aperture Lenses 171\u003c\/p\u003e \u003cp\u003e8.8 Numerical Aperture and Magnification Determine the Light-Gathering Properties of the Microscope Objective 172\u003c\/p\u003e \u003cp\u003e8.9 The Modulation (Contrast) Transfer Function Relates the Relative Contrast to Resolving Power in Fourier, or Frequency, Space 172\u003c\/p\u003e \u003cp\u003e8.10 The Point Spread Function Convolves the Object to Generate the Image 176\u003c\/p\u003e \u003cp\u003e8.11 Problems with the Focus of the Lens Arise from Lens Aberrations 177\u003c\/p\u003e \u003cp\u003e8.12 Refractive Index Mismatch in the Sample Produces Spherical Aberration 182\u003c\/p\u003e \u003cp\u003e8.13 Adaptive Optics Compensate for Refractive Index Changes and Aberration Introduced by Thick Samples 183\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Contrast and Tone Control 189\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 The Subject Determines the Lighting 189\u003c\/p\u003e \u003cp\u003e9.2 Light Measurements Use Two Different Standards: Photometric and Radiometric Units 190\u003c\/p\u003e \u003cp\u003e9.3 The Light Emission and Contrast of Small Objects Limits Their Visibility 194\u003c\/p\u003e \u003cp\u003e9.4 Use the Image Histogram to Adjust the Trade-off Between Depth of Field and Motion Blur 194\u003c\/p\u003e \u003cp\u003e9.5 Use the Camera’s Light Meter to Detect Intrascene Dynamic Range and Set Exposure Compensation 196\u003c\/p\u003e \u003cp\u003e9.6 Light Sources Produce a Variety of Colors and Intensities That Determine the Quality of the Illumination 197\u003c\/p\u003e \u003cp\u003e9.7 Lasers and LEDs Provide Lighting with Specific Color and High Intensity 199\u003c\/p\u003e \u003cp\u003e9.8 Change Light Values with Absorption, Reflectance, Interference, and Polarizing Filters 200\u003c\/p\u003e \u003cp\u003e9.9 Köhler-Illuminated Microscopes Produce Conjugate Planes of Collimated Light from the Source and Specimen 203\u003c\/p\u003e \u003cp\u003e9.10 Reflectors, Diffusers, and Filters Control Lighting in Macro-imaging 207\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Processing with Digital Filters 212\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Image Processing Occurs Before, During, and After Image Acquisition 212\u003c\/p\u003e \u003cp\u003e10.2 Near-Neighbor Operations Modify the Value of a Target Pixel 214\u003c\/p\u003e \u003cp\u003e10.3 Rank Filters Identify Noise and Remove It from Images 215\u003c\/p\u003e \u003cp\u003e10.4 Convolution Can Be an Arithmetic Operation with Near Neighbors 217\u003c\/p\u003e \u003cp\u003e10.5 Deblurring and Background Subtraction Remove Out-of-Focus Features from Optical Sections 221\u003c\/p\u003e \u003cp\u003e10.6 Convolution Operations in Frequency Space Multiply the Fourier Transform of an Image by the Fourier Transform of the Convolution Mask 222\u003c\/p\u003e \u003cp\u003e10.7 Tomographic Operations in Frequency Space Produce Better Back-Projections 224\u003c\/p\u003e \u003cp\u003e10.8 Deconvolution in Frequency Space Removes Blur Introduced by the Optical System But Has a Problem with Noise 224\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Spatial Analysis 231\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Affine Transforms Produce Geometric Transformations 231\u003c\/p\u003e \u003cp\u003e11.2 Measuring Geometric Distortion Requires Grid Calibration 231\u003c\/p\u003e \u003cp\u003e11.3 Distortion Compensation Locally Adds and Subtracts Pixels 231\u003c\/p\u003e \u003cp\u003e11.4 Shape Analysis Starts with the Identification of Landmarks, Then Registration 232\u003c\/p\u003e \u003cp\u003e11.5 Grid Transformations are the Basis for Morphometric Examination of Shape Change in Populations 234\u003c\/p\u003e \u003cp\u003e11.6 Principal Component Analysis and Canonical Variates Analysis Use Measures of Similarity as Coordinates 237\u003c\/p\u003e \u003cp\u003e11.7 Convolutional Neural Networks Can Identify Shapes and Objects Using Deep Learning 238\u003c\/p\u003e \u003cp\u003e11.8 Boundary Morphometrics Analyzes and Mathematically Describes the Edge of the Object 240\u003c\/p\u003e \u003cp\u003e11.9 Measurement of Object Boundaries Can Reveal Fractal Relationships 245\u003c\/p\u003e \u003cp\u003e11.10 Pixel Intensity–Based Colocalization Analysis Reports the Spatial Correlation of Overlapping Signals 246\u003c\/p\u003e \u003cp\u003e11.11 Distance-Based Colocalization and Cluster Analysis Analyze the Spatial Proximity of Objects 250\u003c\/p\u003e \u003cp\u003e11.12 Fluorescence Resonance Energy Transfer Occurs Over Small (1–10 nm) Distances 252\u003c\/p\u003e \u003cp\u003e11.13 Image Correlations Reveal Patterns in Time and Space 253\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Temporal Analysis 260\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Representations of Molecular, Cellular, Tissue, and Organism Dynamics Require Video and Motion Graphics 260\u003c\/p\u003e \u003cp\u003e12.2 Motion Graphics Editors Use Key Frames to Specify Motion 262\u003c\/p\u003e \u003cp\u003e12.3 Motion Estimation Uses Successive Video Frames to Analyze Motion 265\u003c\/p\u003e \u003cp\u003e12.4 Optic Flow Compares the Intensities of Pixels, Pixel Blocks, or Regions Between Frames 266\u003c\/p\u003e \u003cp\u003e12.5 The Kymograph Uses Time as an Axis to Make a Visual Plot of the Object Motion 268\u003c\/p\u003e \u003cp\u003e12.6 Particle Tracking Is a Form of Feature-Based Motion Estimation 269\u003c\/p\u003e \u003cp\u003e12.7 Fluorescence Recovery After Photobleaching Shows Compartment Connectivity and the Movement of Molecules 273\u003c\/p\u003e \u003cp\u003e12.8 Fluorescence Switching Also Shows Connectivity and Movement 276\u003c\/p\u003e \u003cp\u003e12.9 Fluorescence Correlation Spectroscopy and Raster Image Correlation Spectroscopy Can Distinguish between Diffusion and Advection 280\u003c\/p\u003e \u003cp\u003e12.10 Fluorescent Protein Timers Provide Tracking of Maturing Proteins as They Move through Compartments 282\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Three-Dimensional Imaging, Modeling, and Analysis 287\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Three-Dimensional Worlds Are Scalable and Require Both Camera and Actor Views 287\u003c\/p\u003e \u003cp\u003e13.2 Stacking Multiple Adjacent Slices Can Produce a Three-Dimensional Volume or Surface 291\u003c\/p\u003e \u003cp\u003e13.3 Structure-from-Motion Photogrammetry Reconstructs Three-Dimensional Surfaces Using Multiple Camera Views 292\u003c\/p\u003e \u003cp\u003e13.4 Reconstruction of Aligned Images in Fourier Space Produces Three-Dimensional Volumes or Surfaces 295\u003c\/p\u003e \u003cp\u003e13.5 Surface Rendering Produces Isosurface Polygon Meshes Generated from Contoured Intensities 296\u003c\/p\u003e \u003cp\u003e13.6 Texture Maps of Object Isosurfaces Are Images or Movies 299\u003c\/p\u003e \u003cp\u003e13.7 Ray Tracing Follows a Ray of Light Backward from the Eye or Camera to Its Source 300\u003c\/p\u003e \u003cp\u003e13.8 Ray Tracing Shows the Object Based on Internal Intensities or Nearness to the Camera 300\u003c\/p\u003e \u003cp\u003e13.9 Transfer Functions Discriminate Objects in Ray-Traced Three Dimensions 301\u003c\/p\u003e \u003cp\u003e13.10 Four Dimensions, a Time Series of Three-Dimensional Volumes, Can Use Either Ray-Traced or Isosurface Rendering 303\u003c\/p\u003e \u003cp\u003e13.11 Volumes Rendered with Splats and Texture Maps Provide Realistic Object-Ordered Reconstructions 303\u003c\/p\u003e \u003cp\u003e13.12 Analysis of Three-Dimensional Volumes Uses the Same Approaches as Two-Dimensional Area Analysis But Includes Voxel Adjacency and Connectivity 305\u003c\/p\u003e \u003cp\u003e13.13 Head-Mounted Displays and Holograms Achieve an Immersive Three-Dimensional Experience 307\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 3 Image Modalities 313\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Ultrasound Imaging 315\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Ultrasonography Is a Cheap, High-Resolution, Deep-Penetration, Non-invasive Imaging Modality 315\u003c\/p\u003e \u003cp\u003e14.2 Many Species Use Ultrasound and Infrasound for Communication and Detection 315\u003c\/p\u003e \u003cp\u003e14.3 Sound Is a Compression, or Pressure, Wave 316\u003c\/p\u003e \u003cp\u003e14.4 The Measurement of Audible Sound Intensity Is in Decibels 317\u003c\/p\u003e \u003cp\u003e14.5 A Piezoelectric Transducer Creates the Ultrasound Wave 318\u003c\/p\u003e \u003cp\u003e14.6 Different Tissues Have Different Acoustic Impedances 319\u003c\/p\u003e \u003cp\u003e14.7 Sonic Wave Scatter Generates Speckle 321\u003c\/p\u003e \u003cp\u003e14.8 Lateral Resolution Depends on Sound Frequency and the Size and Focal Length of the Transducer Elements 322\u003c\/p\u003e \u003cp\u003e14.9 Axial Resolution Depends on the Duration of the Ultrasound Pulse 323\u003c\/p\u003e \u003cp\u003e14.10 Scatter and Absorption by Tissues Attenuate the Ultrasound Beam 324\u003c\/p\u003e \u003cp\u003e14.11 Amplitude Mode, Motion Mode, Brightness Mode, and Coherent Planar Wave Mode Are the Standard Modes for Clinical Practice 324\u003c\/p\u003e \u003cp\u003e14.12 Doppler Scans of Moving Red Blood Cells Reveal Changes in Vascular Flows with Time and Provide the Basis for Functional Ultrasound Imaging 327\u003c\/p\u003e \u003cp\u003e14.13 Microbubbles and Gas Vesicles Provide Ultrasound Contrast and Have Therapeutic Potential 329\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Magnetic Resonance Imaging 334\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Magnetic Resonance Imaging, Like Ultrasound, Performs Non-invasive Analysis without Ionizing Radiation 334\u003c\/p\u003e \u003cp\u003e15.2 Magnetic Resonance Imaging Is an Image of the Hydrogen Nuclei in Fat and Water 337\u003c\/p\u003e \u003cp\u003e15.3 Magnetic Resonance Imaging Sets up a Net Magnetization in Each Voxel That Is in Dynamic Equilibrium with the Applied Field 338\u003c\/p\u003e \u003cp\u003e15.4 The Magnetic Field Imposed by Magnetic Resonance Imaging Makes Protons Spin Like Tops with the Same Tilt and Determines the Frequency of Precession 338\u003c\/p\u003e \u003cp\u003e15.5 Magnetic Resonance Imaging Disturbs the Net Magnetization Equilibrium and Then Follows the Relaxation Back to Equilibrium 339\u003c\/p\u003e \u003cp\u003e15.6 T2 Relaxation, or Spin–Spin Relaxation, Causes the Disappearance of Transverse (x-y Direction) Magnetization Through Dephasing 342\u003c\/p\u003e \u003cp\u003e15.7 T1 Relaxation, or Spin-Lattice Relaxation, Causes the Disappearance of Longitudinal (z-Direction) Magnetization Through Energy Loss 342\u003c\/p\u003e \u003cp\u003e15.8 Faraday Induction Produces the Magnetic Resonance Imaging Signal (in Volts) with Coils in the x-y Plane 343\u003c\/p\u003e \u003cp\u003e15.9 Magnetic Gradients and Selective Radiofrequency Frequencies Generate Slices in the x, y, and z Directions 343\u003c\/p\u003e \u003cp\u003e15.10 Acquiring a Gradient Echo Image Is a Highly Repetitive Process, Getting Information Independently in the x, y, and z Dimensions 344\u003c\/p\u003e \u003cp\u003e15.11 Fast Low-Angle Shot Gradient Echo Imaging Speeds Up Imaging for T1-Weighted Images 346\u003c\/p\u003e \u003cp\u003e15.12 The Spin-Echo Image Compensates for Magnetic Heterogeneities in the Tissue in T2-Weighted Images 346\u003c\/p\u003e \u003cp\u003e15.13 Three-Dimensional Imaging Sequences Produce Higher Axial Resolution 347\u003c\/p\u003e \u003cp\u003e15.14 Echo Planar Imaging Is a Fast Two-Dimensional Imaging Modality But Has Limited Resolving Power 347\u003c\/p\u003e \u003cp\u003e15.15 Magnetic Resonance Angiography Analyzes Blood Velocity 347\u003c\/p\u003e \u003cp\u003e15.16 Diffusion Tensor Imaging Visualizes and Compares Directional (Anisotropic) Diffusion Coefficients in a Tissue 349\u003c\/p\u003e \u003cp\u003e15.17 Functional Magnetic Resonance Imaging Provides a Map of Brain Activity 350\u003c\/p\u003e \u003cp\u003e15.18 Magnetic Resonance Imaging Contrast Agents Detect Small Lesions That Are Otherwise Difficult to Detect 351\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Microscopy with Transmitted and Refracted Light 355\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Brightfield Microscopy of Living Cells Uses Apertures and the Absorbance of Transmitted Light to Generate Contrast 355\u003c\/p\u003e \u003cp\u003e16.2 Staining Fixed or Frozen Tissue Can Localize Large Polymers, Such as Proteins, Carbohydrates, and Nucleic Acids, But Is Less Effective for Lipids, Diffusible Ions, and Small Metabolites 361\u003c\/p\u003e \u003cp\u003e16.3 Darkfield Microscopy Generates Contrast by Only Collecting the Refracted Light from the Specimen 365\u003c\/p\u003e \u003cp\u003e16.4 Rheinberg Microscopy Generates Contrast by Producing Color Differences between Refracted and Unrefracted Light 368\u003c\/p\u003e \u003cp\u003e16.5 Wave Interference from the Object and Its Surround Generates Contrast in Polarized Light, Differential Interference Contrast, and Phase Contrast Microscopies 369\u003c\/p\u003e \u003cp\u003e16.6 Phase Contrast Microscopy Generates Contrast by Changing the Phase Difference Between the Light Coming from the Object and Its Surround 369\u003c\/p\u003e \u003cp\u003e16.7 Polarized Light Reveals Order within a Specimen and Differences in Object Thickness 374\u003c\/p\u003e \u003cp\u003e16.8 The Phase Difference Between the Slow and Fast Axes of Ordered Specimens Generates Contrast in Polarized Light Microscopy 376\u003c\/p\u003e \u003cp\u003e16.9 Compensators Cancel Out or Add to the Retardation Introduced by the Sample, Making It Possible to Measure the Sample Retardation 379\u003c\/p\u003e \u003cp\u003e16.10 Differential Interference Contrast Microscopy Is a Form of Polarized Light Microscopy That Generates Contrast Through Differential Interference of Two Slightly Separated Beams of Light 383\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Microscopy Using Fluoresced and Reflected Light 390\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Fluorescence and Autofluorescence: Excitation of Molecules by Light Leads to Rapid Re-emission of Lower Energy Light 390\u003c\/p\u003e \u003cp\u003e17.2 Fluorescence Properties Vary Among Molecules and Depend on Their Environment 391\u003c\/p\u003e \u003cp\u003e17.3 Fluorescent Labels Include Fluorescent Proteins, Fluorescent Labeling Agents, and Vital and Non-vital Fluorescence Affinity Dyes 394\u003c\/p\u003e \u003cp\u003e17.4 Fluorescence Environment Sensors Include Single-Wavelength Ion Sensors, Ratio Imaging Ion Sensors, FRET Sensors, and FRET-FLIM Sensors 399\u003c\/p\u003e \u003cp\u003e17.5 Widefield Microscopy for Reflective or Fluorescent Samples Uses Epi-illumination 402\u003c\/p\u003e \u003cp\u003e17.6 Epi-polarization Microscopy Detects Reflective Ordered Inorganic or Organic Crystallites and Uses Nanogold and Gold Beads as Labels 405\u003c\/p\u003e \u003cp\u003e17.7 To Optimize the Signal from the Sample, Use Specialized and Adaptive Optics 405\u003c\/p\u003e \u003cp\u003e17.8 Confocal Microscopes Use Accurate, Mechanical Four-Dimensional Epi-illumination and Acquisition 408\u003c\/p\u003e \u003cp\u003e17.9 The Best Light Sources for Fluorescence Match Fluorophore Absorbance 410\u003c\/p\u003e \u003cp\u003e17.10 Filters, Mirrors, and Computational Approaches Optimize Signal While Limiting the Crosstalk Between Fluorophores 411\u003c\/p\u003e \u003cp\u003e17.11 The Confocal Microscope Has Higher Axial and Lateral Resolving Power Than the Widefield Epi-illuminated Microscope, Some Designs Reaching Superresolution 415\u003c\/p\u003e \u003cp\u003e17.12 Multiphoton Microscopy and Other Forms of Non-linear Optics Create Conditions for Near-Simultaneous Excitation of Fluorophores with Two or More Photons 419\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Extending the Resolving Power of the Light Microscope in Time and Space 427\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Superresolution Microscopy Extends the Resolving Power of the Light Microscope 427\u003c\/p\u003e \u003cp\u003e18.2 Fluorescence Lifetime Imaging Uses a Temporal Resolving Power that Extends to Gigahertz Frequencies (Nanosecond Resolution) 428\u003c\/p\u003e \u003cp\u003e18.3 Spatial Resolving Power Extends Past the Diffraction Limit of Light 429\u003c\/p\u003e \u003cp\u003e18.4 Light Sheet Fluorescence Microscopy Achieves Fast Acquisition Times and Low Photon Dose 432\u003c\/p\u003e \u003cp\u003e18.5 Lattice Light Sheets Increase Axial Resolving Power 435\u003c\/p\u003e \u003cp\u003e18.6 Total Internal Reflection Microscopy and Glancing Incident Microscopy Produce a Thin Sheet of Excitation Energy Near the Coverslip 437\u003c\/p\u003e \u003cp\u003e18.7 Structured Illumination Microscopy Improves Resolution with Harmonic Patterns That Reveal Higher Spatial Frequencies 440\u003c\/p\u003e \u003cp\u003e18.8 Stimulated Emission Depletion and Reversible Saturable Optical Linear Fluorescence Transitions Superresolution Approaches Use Reversibly Saturable Fluorescence to Reduce the Size of the Illumination Spot 447\u003c\/p\u003e \u003cp\u003e18.9 Single-Molecule Excitation Microscopies, Photo-Activated Localization Microscopy, and Stochastic Optical Reconstruction Microscopy Also Rely on Switchable Fluorophores 452\u003c\/p\u003e \u003cp\u003e18.10 MINFLUX Combines Single-Molecule Localization with Structured Illumination to Get Resolution below 10 nm 455\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Electron Microscopy 461\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 Electron Microscopy Uses a Transmitted Primary Electron Beam (Transmission Electron Micrography) or Secondary and Backscattered Electrons (Scanning Electron Micrography) to Image the Sample 461\u003c\/p\u003e \u003cp\u003e19.2 Some Forms of Scanning Electron Micrography Use Unfixed Tissue at Low Vacuums (Relatively High Pressure) 462\u003c\/p\u003e \u003cp\u003e19.3 Both Transmission Electron Micrography and Scanning Electron Micrography Use Frozen or Fixed Tissues 465\u003c\/p\u003e \u003cp\u003e19.4 Critical Point Drying and Surface Coating with Metal Preserves Surface Structures and Enhances Contrast for Scanning Electron Micrography 467\u003c\/p\u003e \u003cp\u003e19.5 Glass and Diamond Knives Make Ultrathin Sections on Ultramicrotomes 468\u003c\/p\u003e \u003cp\u003e19.6 The Filament Type and the Condenser Lenses Control Illumination in Scanning Electron Micrography and Transmission Electron Micrography 471\u003c\/p\u003e \u003cp\u003e19.7 The Objective Lens Aperture Blocks Scattered Electrons, Producing Contrast in Transmission Electron Micrography 474\u003c\/p\u003e \u003cp\u003e19.8 High-Resolution Transmission Electron Micrography Uses Large (or No) Objective Apertures 475\u003c\/p\u003e \u003cp\u003e19.9 Conventional Transmission Electron Micrography Provides a Cellular Context for Visualizing Organelles and Specific Molecules 479\u003c\/p\u003e \u003cp\u003e19.10 Serial Section Transmitted Primary Electron Analysis Can Provide Three-Dimensional Cellular Structures 482\u003c\/p\u003e \u003cp\u003e19.11 Scanning Electron Micrography Volume Microscopy Produces Three-Dimensional Microscopy at Nanometer Scales and Includes In-Lens Detectors and In-Column Sectioning Devices 483\u003c\/p\u003e \u003cp\u003e19.12 Correlative Electron Microscopy Provides Ultrastructural Context for Fluorescence Studies 488\u003c\/p\u003e \u003cp\u003e19.13 Tomographic Reconstruction of Transmission Electron Micrography Images Produces Very Thin (10-nm) Virtual Sections for High-Resolution Three-Dimensional Reconstruction 490\u003c\/p\u003e \u003cp\u003e19.14 Cryo-Electron Microscopy Achieves Molecular Resolving Power (Resolution, 0.1–0.2 Nm) Using Single-Particle Analysis 492\u003c\/p\u003e \u003cp\u003eIndex 497\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407192269143,"sku":"9781119949206","price":135.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119949206.jpg?v=1730498500","url":"https:\/\/bookcurl.com\/products\/imaging-life-9781119949206","provider":"Book Curl","version":"1.0","type":"link"}