1.

Record Nr.

UNINA9910337639203321

Autore

Thanki Rohit M

Titolo

Hybrid and Advanced Compression Techniques for Medical Images / / by Rohit M. Thanki, Ashish Kothari

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019

ISBN

3-030-12575-0

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (107 pages)

Disciplina

616.0754

Soggetti

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

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

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. .

Sommario/riassunto

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.