Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.
To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 6; pp. 957 - 967 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2018
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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=129738988&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 129738988 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jun2018 vid: 56 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 129738988 129738988 NLM29105018 10.1007/s11517-017-1741-8 NLM29105018 129738988 ppf: 957 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction. aug: au: Song, Xiaoying Huang, Qijun Chang, Sheng He, Jin Wang, Hao affil: Engineering Research Center of Metallurgical Automation and Measurement Technology, Wuhan University of Science and Technology, 430081, Wuhan, Hubei, China sug: subj: Diagnostic Imaging Methods Image Processing, Computer Assisted Methods Algorithms Head Wrist Magnetic Resonance Imaging Tomography, X-Ray Computed Regression ab: To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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