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This book provides readers with a sound foundation in both image acquisition and image processing-one of the first books to integrate these topics together. This updated edition includes new chapters on neural networks, convolutional neural networks, affine transform and many new algorithms.
Table des matières
I Introduction to Images and Computing using Python. 1. Introduction to Python. 2. Computing using Python Modules. 3. Image and its Properties. II Image Processing using Python. 5. Image Enhancement. 6. Affine transformation. 7. Fourier Transform. 8 Segmentation. 9 Morphological Operations. 10. Image Measurements. 11. Neural network. 12. Convolutional neural network. III Image Acquisition. 13. X-Ray and Computed Tomography. 14. Magnetic Resonance Imaging. 15. Light Microscopes. 16. Electron Microscopes. Appendices.
A propos de l'auteur
Ravishankar Chityala, Ph.D. is Principal Engineer at IonPath, with eighteen years of experience in image processing. He teaches Python programming and Deep learning using Tensorow at the University of California Santa Cruz, Silicon Valley Campus. Previously, he worked as an image processing consultant at the Minnesota Supercomputing Institute of the University of Minnesota. As an image processing consultant, Dr. Chityala had worked with faculty, students and staff from various departments in the scientific, engineering and medical fields at the University of Minnesota, and his interaction with students had made him aware of their need for greater understanding of and ability to work with image processing and acquisition. Dr. Chityala co-authored Essential Python (Essential Education, California, 2018), also contributed to the writing of Handbook of Physics in Medicine and Biology(CRC Press, Boca Raton, 2009, Robert Splinter). His research interests include image processing, machine learning and deep learning.
Sridevi Pudipeddi, Ph.D. has eleven years of experience teaching undergraduate courses. She teaches Machine Learning with Python and Python for Data Analysis at the University of California Berkeley at San Francisco campus. Dr. Pudipeddi's research interests are in machine learning, applied mathematics and image and text processing. Python's simple syntax and its vast image processing capabilities, along with the need to understand and quantify important experimental information through image acquisition, have inspired her to co-author this book. Dr. Pudipeddi co authored Essential Python (Essential Education, California, 2018).
Résumé
This book provides readers with a sound foundation in both image acquisition and image processing—one of the first books to integrate these topics together. This updated edition includes new chapters on neural networks, convolutional neural networks, affine transform and many new algorithms.
