Rodrigues, J. M. F.Loke, R. E.du Buf, J. M. H.2009-02-132009-02-13200011th Portuguese Conference on Pattern Recognition (RECPAD 2000). - Porto, 11-12 May 2000. - p. 185-189AUT: JRO00913; DUB00865;http://hdl.handle.net/10400.1/131The algorithm developed uses an octree pyramid in which noise is reduced at the expense of the spatial resolution. At a certain level an unsupervised clustering without spatial connectivity constraints is applied. After the classification, isolated voxels and insignificant regions are removed by assigning them to their neighbours. The spatial resolution is then increased by the downprojection of the regions, level by level. At each level the uncertainty of the boundary voxels is minimised by a dynamic selection and classification of these, using an adaptive 3D filtering. The algorithm is tested using different data sets, including NMR data.application/pdfengSegmentação de imagem em 3D3D segmentationBoundary refinementOctreeNMR datajournal article