Interactive Volume Segmentation With Differential Image Foresting Transforms.

dc.creatorFalcão, Alexandre X
dc.creatorBergo, Felipe P G
dc.date2004-Sep
dc.date2015-11-27T12:58:27Z
dc.date2015-11-27T12:58:27Z
dc.date.accessioned2018-03-29T00:59:36Z
dc.date.available2018-03-29T00:59:36Z
dc.identifierIeee Transactions On Medical Imaging. v. 23, n. 9, p. 1100-8, 2004-Sep.
dc.identifier0278-0062
dc.identifier10.1109/TMI.2004.829335
dc.identifierhttp://www.ncbi.nlm.nih.gov/pubmed/15377119
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/195948
dc.identifier15377119
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1296181
dc.descriptionThe absence of object information very often asks for considerable human assistance in medical image segmentation. Many interactive two-dimensional and three-dimensional (3-D) segmentation methods have been proposed, but their response time to user's actions should be considerably reduced to make them viable from the practical point of view. We circumvent this problem in the framework of the image foresting transform (IFT)--a general tool for the design of image operators based on connectivity--by introducing a new algorithm (DIFT) to compute sequences of IFTs in a differential way. We instantiate the DIFT algorithm for watershed-based and fuzzy-connected segmentations under two paradigms (single-object and multiple-object) and evaluate the efficiency gains of both approaches with respect to their linear-time implementation based on the nondifferential IFT. We show that the DIFT algorithm provides efficiency gains from 10 to 17, reducing the user's waiting time for segmentation with 3-D visualization on a common PC from 19-36 s to 2-3 s. We also show that the multiple-object approach is more efficient than the single-object paradigm for both segmentation methods.
dc.description23
dc.description1100-8
dc.languageeng
dc.relationIeee Transactions On Medical Imaging
dc.relationIEEE Trans Med Imaging
dc.rightsfechado
dc.rights
dc.sourcePubMed
dc.subjectAlgorithms
dc.subjectBrain
dc.subjectComputer Graphics
dc.subjectHumans
dc.subjectImage Interpretation, Computer-assisted
dc.subjectImaging, Three-dimensional
dc.subjectMagnetic Resonance Imaging
dc.subjectOnline Systems
dc.subjectPattern Recognition, Automated
dc.subjectReproducibility Of Results
dc.subjectSensitivity And Specificity
dc.subjectSoftware
dc.subjectUser-computer Interface
dc.titleInteractive Volume Segmentation With Differential Image Foresting Transforms.
dc.typeArtículos de revistas


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