Hybrid and Advanced Compression Techniques for Medical Images [electronic resource] /
Thanki, Rohit M.author.(orcid)0000-0002-0645-6266https://orcid.org/0000-0002-0645-6266aut
Kothari, Ashish.author.
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.
Chapter 1. Data Compression and its Application in Medical Imaging -- Chapter 2. Classification in Data Compression -- Chapter 3.Mathematical Preliminaries -- Chapter 4.Conventional Compression Techniques for Medical Images -- Chapter 5. CS Theory based Compression Techniques for Medical Images -- Chapter 6. Color Medical Image Compression Techniques. .
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.
Biomedical engineering.
Signal processing.
Image processing.
Speech processing systems.
Radiology.
Optical data processing.
Medical physics.
Radiation.
Biomedical Engineering and Bioengineering.
Signal, Image and Speech Processing.
Biomedical Engineering/Biotechnology.
Imaging / Radiology.
Image Processing and Computer Vision.
Medical and Radiation Physics.