Novel framework for registration of pedobarographic image data.
This article presents a framework to register (or align) plantar pressure images based on a hybrid registration approach, which first establishes an initial registration that is subsequently improved by the optimization of a selected image (dis)similarity measure. The initial registration has two di...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 49; no. 3; pp. 313 - 324 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Mar2011
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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=104570422&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104570422 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Mar2011 vid: 49 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104570422 NLM21046271 2010967513 10.1007/s11517-010-0700-4 NLM21046271 104570422 ppf: 313 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Novel framework for registration of pedobarographic image data. aug: au: Oliveira FP Tavares JM Oliveira, Francisco P M Tavares, João Manuel R S affil: Faculdade de Engenharia da Universidade do Porto, Instituto de Engenharia Mecânica e Gestão Industrial, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal sug: subj: Foot Physiology Image Processing, Computer Assisted Methods Algorithms Biomechanics Pressure ab: This article presents a framework to register (or align) plantar pressure images based on a hybrid registration approach, which first establishes an initial registration that is subsequently improved by the optimization of a selected image (dis)similarity measure. The initial registration has two different solutions: one based on image contour matching and the other on image cross-correlation. In the final registration, a multidimensional optimization algorithm is applied to one of the following (dis)similarity measures: the mean squared error (MSE), the mutual information, and the exclusive or (XOR). The framework has been applied to intra- and inter-subject registration. In the former, the framework has proven to be extremely accurate and fast (<70 ms on a normal PC notebook), and obtained superior XOR and identical MSE values compared to the best values reported in previous studies. Regarding the inter-subject registration, by using rigid, similarity, affine, projective, and polynomial (up to the fourth degree) transformations, the framework significantly optimized the image (dis)similarity measures. Thus, it is considered to be very accurate, fast, and robust in terms of noise, as well as being extremely versatile, all of which are regarded as essential features for near-real-time applications. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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