Projection-Based Medical Image Compression for Telemedicine Applications.
Recent years have seen great development in the field of medical imaging and telemedicine. Despite the developments in storage and communication technologies, compression of medical data remains challenging. This paper proposes an efficient medical image compression method for telemedicine. The prop...
| Publicado en: | Journal of Digital Imaging Vol. 28; no. 2; pp. 146 - 160 |
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| Autores principales: | , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2015
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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=103774896&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103774896 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2015 vid: 28 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 103774896 101556456 10.1007/s10278-014-9731-y NLM25236913 PMC4359194 103774896 ppf: 146 ppct: 14 formats: fmt: @attributes: type: P tig: atl: Projection-Based Medical Image Compression for Telemedicine Applications. aug: au: Juliet, Sujitha Rajsingh, Elijah Ezra, Kirubakaran affil: Department of Information Technology, Karunya University, Coimbatore India sug: subj: Digital Compression Methods Teleradiology Algorithms Quality Assurance Evaluation Research Comparative Studies Scales Human ab: Recent years have seen great development in the field of medical imaging and telemedicine. Despite the developments in storage and communication technologies, compression of medical data remains challenging. This paper proposes an efficient medical image compression method for telemedicine. The proposed method takes advantage of Radon transform whose basis functions are effective in representing the directional information. The periodic re-ordering of the elements of Radon projections requires minimal interpolation and preserves all of the original image pixel intensities. The dimension-reducing property allows the conversion of 2D processing task to a set of simple 1D task independently on each of the projections. The resultant Radon coefficients are then encoded using set partitioning in hierarchical trees (SPIHT) encoder. Experimental results obtained on a set of medical images demonstrate that the proposed method provides competing performance compared with conventional and state-of-the art compression methods in terms of compression ratio, peak signal-to-noise ratio (PSNR), and computational time. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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