Lawrence R. Griffing

Imaging Life

Image Acquisition and Analysis in Biology and Medicine

• Gebundenes Buch

Produktbeschreibung

Hands-on resource to understand and successfully process biological image data

In Imaging Life: Image Acquisition and Analysis in Biology and Medicine, distinguished biologist Dr. Lawrence R. Griffing delivers a comprehensive and accessible exploration of scientific imaging, including but not limited to the different scientific imaging technologies, image processing, and analysis. The author discusses technical features, challenges, and solutions of the various imaging modalities to obtain the best possible image.

Divided into three sections, the book opens with the basics such as the various image media, their representation and evaluation. It explains in exceptional detail pre- and postprocessing of an image. The last section concludes with common microscopic and biomedical imaging modalities in light of technical limitations and solutions to achieve the best possible image acquisition of the specimen.

Imaging Life: Image Acquisition and Analysis in Biology and Medicine is written specifically for readers with limited mathematical and programming backgrounds and includes tutorials on image processing in relevant chapters. It also contains exercises in the use of popular, open-source software.
_ A thorough introduction to imaging methods, technical features, challenges, and solutions to successfully capture biological images
_ Offers tutorials on image processing using open-source software in relevant chapter
_ Discusses details of acquisition needs and image media covering pixels, pixel values, contrast, tonal range, and image formats
_ In-depth presentation of microscopic and biomedical imaging modalities

Perfect for professionals and students in the biological sciences and engineering, Imaging Life: Image Acquisition and Analysis in Biology and Medicine is an ideal resource for research labs, biotech companies, and equipment vendors.

Produktdetails

• Verlag: Wiley & Sons
• Artikelnr. des Verlages: 1A119949200
• 1. Auflage
• Seitenzahl: 544
• Erscheinungstermin: 11. April 2023
• Englisch
• Abmessung: 281mm x 219mm x 31mm
• Gewicht: 1722g
• ISBN-13: 9781119949206
• ISBN-10: 1119949203
• Artikelnr.: 40783320

Autorenporträt

Lawrence R. Griffing, PhD, is Associate Professor of Biology at Texas A&M University. He formerly served as Program Director for Cell Biology at the National Science Foundation and was Associate Director of the ITS-Center for Teaching and Learning. He teaches several undergraduate courses and graduate seminars on plant cell biology, 3D biology, and biological imaging.

Inhaltsangabe

Preface xii

Acknowledgments xiv

About the Companion Website xv

Section 1 Image Acquisition 1

1 Image Structure and Pixels 3

1.1 The Pixel Is the Smallest Discrete Unit of a Picture 3

1.2 The Resolving Power of a Camera or Display Is the Spatial Frequency of Its Pixels 6

1.3 Image Legibility Is the Ability to Recognize Text in an Image by Eye 7

1.4 Magnification Reduces Spatial Frequencies While Making Bigger Images 9

1.5 Technology Determines Scale and Resolution 11

1.6 The Nyquist Criterion: Capture at Twice the Spatial Frequency of the Smallest Object Imaged 12

1.7 Archival Time, Storage Limits, and the Resolution of the Display Medium Influence Capture and Scan Resolving Power 13

1.8 Digital Image Resizing or Scaling Match the Captured Image Resolution to the Output Resolution 14

1.9 Metadata Describes Image Content, Structure, and Conditions of Acquisition 16

2 Pixel Values and Image Contrast 20

2.1 Contrast Compares the Intensity of a Pixel with That of Its Surround 20

2.2 Pixel Values Determine Brightness and Color 21

2.3 The Histogram Is a Plot of the Number of Pixels in an Image at Each Level of Intensity 24

2.4 Tonal Range Is How Much of the Pixel Depth Is Used in an Image 25

2.5 The Image Histogram Shows Overexposure and Underexposure 26

2.6 High-Key Images Are Very Light, and Low-Key Images Are Very Dark 27

2.7 Color Images Have Various Pixel Depths 27

2.8 Contrast Analysis and Adjustment Using Histograms Are Available in Proprietary and Open-Source Software 29

2.9 The Intensity Transfer Graph Shows Adjustments of Contrast and Brightness Using Input and Output Histograms 30

2.10 Histogram Stretching Can Improve the Contrast and Tonal Range of the Image without Losing Information 32

2.11 Histogram Stretching of Color Channels Improves Color Balance 32

2.12 Software Tools for Contrast Manipulation Provide Linear, Non-linear, and Output-Visualized Adjustment 34

2.13 Different Image Formats Support Different Image Modes 36

2.14 Lossless Compression Preserves Pixel Values, and Lossy Compression Changes Them 37

3 Representation and Evaluation of Image Data 42

3.1 Image Representation Incorporates Multiple Visual Elements to Tell a Story 42

3.2 Illustrated Confections Combine the Accuracy of a Typical Specimen with a Science Story 42

3.3 Digital Confections Combine the Accuracy of Photography with a Science Story 45

3.4 The Video Storyboard Is an Explicit Visual Confection 48

3.5 Artificial Intelligence Can Generate Photorealistic Images from Text Stories 48

3.6 Making Images Believable: Show Representative Images and State the Acquisition Method 50

3.7 Making Images Understood: Clearly Identify Regions of Interest with Suitable Framing, Labels, and Image Contrast 51

3.8 Avoid Dequantification and Technical Artifacts While Not Hesitating to Take the Picture 55

3.9 Accurate, Reproducible Imaging Requires a Set of Rules and Guidelines 56

3.10 The Structural Similarity Index Measure Quantifies Image Degradation 57

4 Image Capture by Eye 61

4.1 The Anatomy of the Eye Limits Its Spatial Resolution 61

4.2 The Dynamic Range of the Eye Exceeds 11 Orders of Magnitude of Light Intensity, and Intrascene Dynamic Range Is about 3 Orders 63

4.3 The Absorption Characteristics of Photopigments of the Eye Determines Its Wavelength Sensitivity 63

4.4 Refraction and Reflection Determine the Optical Properties of Materials 67

4.5 Movement of Light Through the Eye Depen