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Hybrid and Advanced Compression Techniques for Medical Images de Rohit M. Thanki

Hybrid and Advanced Compression Techniques for Medical Images

Autor Rohit M. Thanki, Ashish Kothari
en Limba Engleză Hardback – 5 mar 2019
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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Specificații

ISBN-13: 9783030125745
ISBN-10: 3030125742
Pagini: 100
Ilustrații: XVII, 95 p. 43 illus., 9 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.34 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Cuprins

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. 

Notă biografică

Dr. Rohit M. Thanki obtained his Ph.D. in Multibiometric System Security using CS Theory and Watermarking from C. U. Shah University, Wadhwan city, Gujarat. His primary areas of research are Digital Watermarking, Biometric Systems, Security, Compressive Sensing, Pattern Recognition, and Image Processing. He has published seven books, seven book chapters, and 30 research papers in refereed and indexed journals and international and national conferences. His international recognition includes his professional memberships and services in refereed organizations, program committees and as a reviewer for journals published by IEEE, Elsevier, Taylor & Francis, Springer, and IGI-Global.
 Dr. Ashish M. Kothari obtained his Ph.D. in Digital Video Watermarking from JJT University, Rajasthan, India. He is an Associate professor and Head of Electronics and Communication Engineering at Atmiya Institute of Technology and Science, Rajkot, Gujarat, India. He is also  a recognized Ph.D. supervisor at Gujarat Technological University, Ahmedabad. His primary areas of research are Image Processing, Video Processing, Digital Watermarking, and Signal Processing. He has published one book and more than 25 research papers in refereed and indexed journals and conferences at the international and national level.

Textul de pe ultima copertă

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.

Caracteristici

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.