9783030125745-3030125742-Hybrid and Advanced Compression Techniques for Medical Images

Hybrid and Advanced Compression Techniques for Medical Images

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Summary

Hybrid and Advanced Compression Techniques for Medical Images (ISBN-13: 9783030125745 and ISBN-10: 3030125742), written by authors Ashish Kothari, Rohit M. Thanki, was published by Springer in 2019. With an overall rating of 3.9 stars, it's a notable title among other AI & Machine Learning (Graphics & Design, Graphics & Multimedia, Programming, Software Design, Testing & Engineering, Voice Recognition, Software, Biochemistry, Chemistry, Nuclear Physics, Physics, Medical Technology, Allied Health Professions, Computer Science) books. You can easily purchase or rent Hybrid and Advanced Compression Techniques for Medical Images (Hardcover) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This book introduces advanced and hybrid compression techniques specifically used for medical images. The book discusses conventional compression and compressive sensing (CS) theory based approaches that are designed and implemented using various image transforms, such as: Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Singular Value Decomposition (SVD) and greedy based recovery algorithm. The authors show how these techniques provide simulation results of various compression techniques for different types of medical images, such as MRI, CT, US, and x-ray images. Future research directions are provided for medical imaging science. The book will be a welcomed reference for engineers, clinicians, and research students working with medical image compression in the biomedical imaging field. 

  • Covers various algorithms for data compression and medical image compression;
  • Provides simulation results of compression algorithms for different types of medical images;
  • Provides study of compressive sensing theory for compression of medical images.

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