dc.creatorBergo F.P.G.
dc.creatorFalcao A.X.
dc.date2006
dc.date2015-06-30T18:02:36Z
dc.date2015-11-26T14:16:35Z
dc.date2015-06-30T18:02:36Z
dc.date2015-11-26T14:16:35Z
dc.date.accessioned2018-03-28T21:17:34Z
dc.date.available2018-03-28T21:17:34Z
dc.identifier0780395778; 9780780395770
dc.identifier2006 3rd Ieee International Symposium On Biomedical Imaging: From Nano To Macro - Proceedings. , v. 2006, n. , p. 486 - 489, 2006.
dc.identifier
dc.identifier
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-33750943215&partnerID=40&md5=f50e3a2fee8ee2b4a8061564e5af7862
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/102801
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/102801
dc.identifier2-s2.0-33750943215
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1243101
dc.descriptionCurvilinear reformatting is known as the best non-invasive technique for diagnosis of dysplastic lesions of the brain. It consists of computing surfaces that follow the brain's curvature at various depths, making the diagnosis possible by visual inspection of the voxel intensities on these surfaces. Traditional approaches require user intervention and present curvature artifacts. We present a new method for curvilinear reformatting that solves both problems. It uses a graph-based approach to segment the brain, extract its envelope, and compute the isosurfaces at all possible depths by euclidean distance transform. It requires no user input, no ad-hoc parameters, and takes less than 1 minute to run on a common PC. © 2006 IEEE.
dc.description2006
dc.description
dc.description486
dc.description489
dc.descriptionBarkovich, A.J., Rowley, H.A., Andermann, F., MR in partial epilepsy: Value of high-resolution volumetric techniques (1995) American Journal of Neuroradiology, 16, pp. 339-343. , Feb
dc.descriptionBastos, A.C., Comeau, R.M., Andermann, F., Melanson, D., Cendes, F., Dubeau, F., Fontaine, S., Olivier, A., Diagnosis of subtle focal dysplastic lesions: Curvilinear reformatting from three-dimensional magnetic resonance imaging (1999) Annals of Neurology, 46 (1), pp. 88-94
dc.descriptionColombo, N., Tassi, L., Galli, C., Citterio, A., Lo Russo, G., Scialfa, G., Spreafico, R., Focal cortical dysplasias: MR imaging, histopathologic, and clinical correlations in surgically treated patients with epilepsy (2003) American Journal of Neuroradiology, 24, pp. 724-733. , Apr
dc.descriptionBrainSight, , http://www.rogue-research.com/B/epilepsy.htm
dc.descriptionFrackowiak, R.S.J., Friston, K.J., Frith, C., Dolan, R., Price, C.J., Zeki, S., Ashburner, J., Penny, W.D., (2003) Human Brain Function, , Academic Press, 2nd edition
dc.descriptionBueno, G., Musse, O., Heitz, F., Armspach, J.P., Three-dimensional segmentation of anatomical structures in MR images on large data bases (2001) Magnetic Resonance Imaging, 19, pp. 73-88
dc.descriptionDougherty, E.R., Lotufo, R.A., (2003) Hands-on Morphological Image Processing, , SPIE Press, Bellingham, WA
dc.descriptionFalcão, A.X., Stolfi, J., Lotufo, R.A., The image foresting transform: Theory, algorithms, and applications (2004) IEEE Trans. on Pattern Analysis and Machine Intelligence, 26 (1), pp. 19-29
dc.descriptionFalcão, A.X., Bergo, F.P.G., Miranda, P.A.V., Image segmentation by tree pruning (2004) Proc. of the XVII Brazillian Symposium on Computer Graphics and Image Processing., pp. 65-71. , Oct , IEEE
dc.descriptionFalcão, A.X., Miranda, P.A.V., Bergo, F.P.G., (2005) Automatic Object Detection by Tree Pruning, , Tech. Rep. IC-05-19, Institute of Computing, University of Campinas, Sep
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dc.languageen
dc.publisher
dc.relation2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
dc.rightsfechado
dc.sourceScopus
dc.titleFast And Automatic Curvilinear Reformatting Of Mr Images Of The Brain For Diagnosis Of Dysplastic Lesions
dc.typeActas de congresos


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