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Hybrid and advanced compression techniques for medical images

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dc.contributor.author Kothari, Ashish
dc.date.accessioned 2025-01-02T07:00:06Z
dc.date.available 2025-01-02T07:00:06Z
dc.date.issued 2019
dc.identifier.uri http://10.9.150.37:8080/dspace//handle/atmiyauni/2260
dc.description.abstract 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. en_US
dc.language.iso en en_US
dc.publisher Springer Nature en_US
dc.title Hybrid and advanced compression techniques for medical images en_US
dc.type Book en_US


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