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 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 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.
{"title":"Image Processing and Acquisition using Python","authors":"Ravishankar Chityala, Sridevi Pudipeddi","doi":"10.1201/b16533","DOIUrl":"https://doi.org/10.1201/b16533","url":null,"abstract":"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 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 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.","PeriodicalId":166422,"journal":{"name":"Image Processing and Acquisition using Python","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126244711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-04-05DOI: 10.1201/9781420075250-C26
R. Chityala
{"title":"X-Ray and Computed Tomography","authors":"R. Chityala","doi":"10.1201/9781420075250-C26","DOIUrl":"https://doi.org/10.1201/9781420075250-C26","url":null,"abstract":"","PeriodicalId":166422,"journal":{"name":"Image Processing and Acquisition using Python","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133435525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：