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Journal ArticleDOI

3-D medical image compression using 3-D wavelet coders

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TLDR
It is found from the test results that the 3-D Cohen-Daubechies-Feauveau 9/7 symmetric wavelet along with the3-D SPIHT encoder yields the best compression result.
About
This article is published in Digital Signal Processing.The article was published on 2011-01-01. It has received 49 citations till now. The article focuses on the topics: Discrete wavelet transform & Wavelet packet decomposition.

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Citations
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Classification of epileptic seizures using wavelet packet log energy and norm entropies with recurrent Elman neural network classifier.

TL;DR: This specific proposed study makes use of wavelet packet based log and norm entropies with a recurrent Elman neural network (REN) for the automated detection of epileptic seizures and found that thewavelet packet log entropy with REN classifier yielded a classification accuracy of 99.85%.
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A novel medical image compression using Ripplet transform

TL;DR: A novel compression method using Ripplet transform to represent singularities along arbitrarily shaped curves and Set Partitioning in Hierarchical Trees encoder to encode the significant coefficients to achieve high compression ratio.
Journal ArticleDOI

Versatile Approaches for Medical Image Compression: A Review

TL;DR: This paper focuses over the current status of these compression strategies with new hybrid approaches, performance parameters, legal issues and their applications in enhancing the medical technology.
Journal ArticleDOI

Multi-Objective Genetic Algorithms to Find Most Relevant Volumes of the Brain Related to Alzheimer's Disease and Mild Cognitive Impairment.

TL;DR: The optimization of volumes of interest (VOIs) to extract three-dimensional textures from Magnetic Resonance Image (MRI) in order to diagnose AD, Mild Cognitive Impairment converter (MCIc), Mild Cognitiveimpairment nonconverter (MCInc) and Normal subjects obtains excellent results in multi-class classification achieving accuracies of 94.4% and extracting significant information on the location of the most relevant points of the brain.

A survey on various medical image compression techniques

TL;DR: The need for an efficient technique for compression of Images ever increasing because the transmission & storage of images is ever increasing.
References
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Journal ArticleDOI

Image quality assessment: from error visibility to structural similarity

TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.

The lifting scheme: A construction of second generation wavelets

Wim Sweldens
TL;DR: The lifting scheme is presented, a simple construction of second generation wavelets; these are wavelets that are not necessarily translates and dilates of one fixed function, and can be adapted to intervals, domains, surfaces, weights, and irregular samples.
Journal ArticleDOI

The lifting scheme: a construction of second generation wavelets

TL;DR: The lifting wavelet as discussed by the authors is a simple construction of second generation wavelets that can be adapted to intervals, domains, surfaces, weights, and irregular samples, and it leads to a faster, in-place calculation of the wavelet transform.
Book

Image and Video Compression Standards: Algorithms and Architectures

TL;DR: An introduction to the algorithms and architectures that form the underpinnings of the image and video compressions standards, including JPEG, H.261 and H.263, while fully addressing the architecturalconsiderations involved when implementing these standards.
Book

Hyperspectral Data Exploitation: Theory and Applications

Chein-I Chang
TL;DR: Chang et al. as mentioned in this paper proposed a semi-supervised support vector machine (SVM) for the classification of hyperspectral remote sensing images, which achieved state-of-the-art performance.
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