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|a Image processing and acquisition using Python /
|c Ravishankar Chityala, Sridevi Pudipeddi.
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|b CRC Press,
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|a Chapman & Hall/CRC mathematical and computational imaging sciences
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|a "Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing--one of the first books to integrate these topics together. By improving readers' knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples. A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The last part describes image acquisition using various modalities, such as X-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry"--
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505 |
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|a Introduction to Images and Computing using Python; Introduction to Python; Introduction; What Is Python?; Python Environments; Running a Python Program; Basic Python Statements and Data Types Computing using Python Modules; Introduction; Python Modules; Numpy; Scipy; Matplotlib; Python Imaging Library; Scikits; Python OpenCV Module Image and Its Properties; Introduction; Image and Its Properties; Image Types; Data Structures for Image Analysis; Programming Paradigm Image Processing using Python; Spatial Filters; Introduction; Filtering; Edge Detection using Derivatives Image Enhancement; Introduction; Pixel Transformation; Image Inverse; Power Law Transformation; Log Transformation; Histogram Equalization; Contrast Stretching Fourier Transform.
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505 |
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|a ; Introduction; Definition of Fourier Transform; Two-Dimensional Fourier Transform; Convolution; Filtering in Frequency Domain Segmentation; Introduction; Histogram-Based Segmentation; Region-Based Segmentation; Segmentation Algorithm for Various Modalities Morphological Operations; Introduction; History; Dilation; Erosion; Grayscale Dilation and Erosion; Opening and Closing; Hit-or-Miss; Thickening and Thinning Image Measurements; Introduction; Labeling; Hough Transform; Template Matching Image Acquisition; X-Ray and Computed Tomography ; Introduction; History; X-Ray Generation; Material Properties; X-Ray Detection; X-Ray Imaging Modes; Computed Tomography (CT); Hounsfield Unit (HU); Artifacts Magnetic Resonance Imaging; Introduction; Laws Governing NMR and MRI; Material.
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505 |
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|a Properties; NMR Signal Detection; MRI Signal Detection or MRI Imaging; MRI Construction; T1, T2, and Proton Density Image; MRI Modes or Pulse Sequence; MRI Artifacts Light Microscopes; Introduction; Physical Principles; Construction of a Wide-Field Microscope; Epi-Illumination; Fluorescence Microscope; Confocal Microscopes; Nipkow Disk Microscopes; Confocal or Wide-Field? Electron Microscopes; Introduction; Physical Principles; Construction of EM; Specimen Preparations; Construction of TEM; Construction of SEM; Appendix A: Installing Python Distributions; Appendix B: Parallel Programming Using MPI4Py; Appendix C: Introduction to ImageJ; Appendix D: MATLAB and Numpy Functions Index A Summary and Exercises appear at the end of each chapter.
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