A comparison of wavelet and joint photographic experts group lossy compression methods applied to medical images...Proceedings of the 16th Symposium for Computer Applications in Radiology. 'PACS: Performance Improvement in Radiology.' Houston TX, May 6-9, 1999
This presentation focuses on the quantitative comparison of three lossy compression methods applied to a variety of 12-bit medical images. One Joint Photographic Exports Group (JPEG) and two wavelet algorithms were used on a population of 60 images. The medical images were obtained in Digital Imagin...
| Publicado en: | Journal of Digital Imaging Vol. 12; pp. 14 - 18 |
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| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
May1999 Supplement
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=107211395&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 107211395 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: May1999 Supplement vid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 107211395 107211395 1999061188 NLM10342156 107211395 ppf: 14 ppct: 4 formats: tig: atl: A comparison of wavelet and joint photographic experts group lossy compression methods applied to medical images...Proceedings of the 16th Symposium for Computer Applications in Radiology. 'PACS: Performance Improvement in Radiology.' Houston TX, May 6-9, 1999 aug: au: Iyriboz TA Zukoski MJ Hopper KD Stagg PL affil: Department of Radiology, 500 University Dr, Penn State Geisinger Health System and Penn State College of Medicine, Hershey, PA 17033-1850 sug: subj: Diagnostic Imaging Image Processing, Computer Assisted Methods Radiographic Image Enhancement Signal Processing, Computer Assisted Software Algorithms Comparative Studies Paired T-Tests Human ab: This presentation focuses on the quantitative comparison of three lossy compression methods applied to a variety of 12-bit medical images. One Joint Photographic Exports Group (JPEG) and two wavelet algorithms were used on a population of 60 images. The medical images were obtained in Digital Imaging and Communications in Medicine (DICOM) file format and ranged in matrix size from 256 x 256 (magnetic resonance [MR]) to 2,560 x 2,048 (computed radiography [CR], digital radiography [DR], etc). The algorithms were applied to each image at multiple levels of compression such that comparable compressed file sizes were obtained at each level. Each compressed image was then decompressed and quantitative analysis was performed to compare each compressed-then-decompressed image with its corresponding original image. The statistical measures computed were sum of absolute differences, sum of squared differences, and peak signal-to-noise ratio (PSNR). Our results verify other research studies which show that wavelet compression yields better compression quality at constant compressed file sizes compared with JPEG. The DICOM standard does not yet include wavelet as a recognized lossy compression standard. For implementers and users to adopt wavelet technology as part of their image management and communication installations, there has to be significant differences in quality and compressibility compared with JPEG to justify expensive software licenses and the introduction of proprietary elements in the standard. Our study shows that different wavelet implementations vary in their capacity to differentiate themselves from the old, established lossy JPEG. Copyright (c) 1999 by W.B. Saunders Company pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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