Medical Image Processing Using Novel Wavelet Filters Based on Atomic Functions: Optimal Medical Image Compression

Landín, Cristina Juárez; Reyes, Magally Martínez; Martín, Anabelem Soberanes; Valdovinos, R. M.; Ramírez, José Luis Sánchez; Ponomaryov, Volodymyr; Soto, María Dolores Torres

doi:10.1007/978-1-4419-7046-6_50

Cited by 4 publications

(1 citation statement)

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“…can be useful in compression of full color digital images. It should be also mentioned that application of atomic functions to compression of medical images was considered in [13].…”

Section: Introductionmentioning

confidence: 99%

Discrete Atomic Compression of Digital Images

Brysina

Makarichev

2018

reks

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The subject matter of this paper is the discrete atomic compression (DAC) of digital images, which is a lossy compression process based on the discrete atomic transform (DAT). The goal is to investigate the efficiency of the DAC algorithm. We solve the following tasks: to develop a general compression scheme using discrete atomic transform and to compare the results of DAC and JPEG algorithms. In this article, we use the methods of digital image processing, atomic function theory, and approximation theory. To compare the efficiency of DAC with the JPEG compression algorithm we use the sets of the classic test images and the classic aerial images. We analyze compression ratio (CR) and loss of quality, using uniform (U), root mean square (RMS) and peak signal to noise ratio (PSNR) metrics. DAC is an algorithm with flexible parameters. In this paper, we use “Optimal” and “Allowable” modes of this algorithm and compare them with the corresponding modes of JPEG. We obtain the following results: 1) DAC is much better than JPEG by the U-criterion of quality loss; 2) there are no significant differences between DAC and JPEG by RMS and PSNR criterions; 3) the compression ratio of DAC is much higher than the compression ratio of JPEG. In other words, the DAC algorithm saves more memory than the JPEG compression algorithm with not worse quality results. These results are due to the fundamental properties of atomic functions such as good approximation properties, the high order of smoothness and existence of locally supported basis in the spaces of atomic functions. Since generalized Fup-functions have the same convenient properties, it is clear that such compression results can be achieved by application of a generalized discrete atomic transform, which is based on these functions. We also discuss the obtained results in the terms of approximation theory and function theory. Conclusions: 1) it is possible to achieve better results with DAC than with JPEG; 2) application of DAC to image compression is more preferable than JPEG in the case when it is planned to use recognition algorithms; 3) further development and investigation of the DAC algorithm are promising

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“…can be useful in compression of full color digital images. It should be also mentioned that application of atomic functions to compression of medical images was considered in [13].…”

Section: Introductionmentioning

confidence: 99%

Discrete Atomic Compression of Digital Images

Brysina

Makarichev

2018

reks

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On the Applications of the Special Class of Atomic Functions: Practical Aspects and Perspectives

Makarichev

Brysina

2021

Lecture Notes in Networks and Systems

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Application of wavelets to the evaluation of phantom images for mammography quality control

et al. 2012

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The main goal of this work was to develop a methodology for the computed analysis of American College of Radiology (ACR) mammographic phantom images, to be used in a quality control (QC) program of mammographic services. Discrete wavelet transform processing was applied to enhance the quality of images from the ACR mammographic phantom and to allow a lower dose for automatic evaluations of equipment performance in a QC program. Regions of interest (ROIs) containing phantom test objects (e.g., masses, fibers and specks) were focalized for appropriate wavelet processing, which highlighted the characteristics of structures present in each ROI. To minimize false-positive detection, each ROI in the image was submitted to pattern recognition tests, which identified structural details of the focalized test objects. Geometric and morphologic parameters of the processed test object images were used to quantify the final level of image quality. The final purpose of this work was to establish the main computational procedures for algorithms of quality evaluation of ACR phantom images. These procedures were implemented, and satisfactory agreement was obtained when the algorithm scores for image quality were compared with the results of assessments by three experienced radiologists. An exploratory study of a potential dose reduction was performed based on the radiologist scores and on the algorithm evaluation of images treated by wavelet processing. The results were comparable with both methods, although the algorithm had a tendency to provide a lower dose reduction than the evaluation by observers. Nevertheless, the objective and more precise criteria used by the algorithm to score image quality gave the computational result a higher degree of confidence. The developed algorithm demonstrates the potential use of the wavelet image processing approach for objectively evaluating the mammographic image quality level in routine QC tests. The implemented computational procedures could also enable the performance of advanced analyses to study potential dose reduction in a routine service.

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Medical Image Processing Using Novel Wavelet Filters Based on Atomic Functions: Optimal Medical Image Compression

Cited by 4 publications

References 4 publications

Discrete Atomic Compression of Digital Images

Discrete Atomic Compression of Digital Images

On the Applications of the Special Class of Atomic Functions: Practical Aspects and Perspectives

Application of wavelets to the evaluation of phantom images for mammography quality control

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