dc.contributor.author | RAMASWAMI, MANI | en |
dc.contributor.author | PAN, KANGYU | en |
dc.contributor.author | KOKARAM, ANIL | en |
dc.contributor.author | CORRIGAN, DAVID | en |
dc.date.accessioned | 2012-03-01T16:28:19Z | |
dc.date.available | 2012-03-01T16:28:19Z | |
dc.date.issued | 2012 | en |
dc.date.submitted | 2012 | en |
dc.identifier.citation | Kangyu Pan, David Corrigan, Jens Hillebrand, Mani Ramaswami, and Anil Kokaram, A wavelet-based Bayesian framework for 3D object segmentation in microscopy, Proceedings of SPIE, 8227, 2012, art. no. 82271O | en |
dc.identifier.other | Y | en |
dc.identifier.uri | http://hdl.handle.net/2262/62460 | |
dc.description | PUBLISHED | en |
dc.description.abstract | In confocal microscopy, target objects are labeled with fluorescent markers in the living specimen, and usually appear with irregular brightness in the observed images. Also, due to the existence of out-of-focus objects in the image, the segmentation of 3-D objects in the stack of image slices captured at different depth levels of the specimen is still heavily relied on manual analysis. In this paper, a novel Bayesian model is proposed for segmenting 3-D synaptic objects from given image stack. In order to solve the irregular brightness and out-offocus problems, the segmentation model employs a likelihood using the luminance-invariant 'wavelet features' of image objects in the dual-tree complex wavelet domain as well as a likelihood based on the vertical intensity profile of the image stack in 3-D. Furthermore, a smoothness 'frame' prior based on the a priori knowledge of the connections of the synapses is introduced to the model for enhancing the connectivity of the synapses. As a result, our model can successfully segment the in-focus target synaptic object from a 3D image stack with irregular brightness. | en |
dc.description.sponsorship | This work was supported by the Science Foundation Ireland PI Programme: SFI-PI 08/IN.1/I2112 | en |
dc.format.extent | art. no. 82271O | en |
dc.language.iso | en | en |
dc.relation.ispartofseries | Proceedings of SPIE | en |
dc.relation.ispartofseries | 8227 | en |
dc.rights | Y | en |
dc.subject | Microscopy | en |
dc.subject | 3-D objects | en |
dc.title | A wavelet-based Bayesian framework for 3D object segmentation in microscopy | en |
dc.type | Journal Article | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/akokaram | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/ramaswam | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/dacorrig | en |
dc.identifier.rssinternalid | 78527 | en |
dc.subject.TCDTheme | Nanoscience & Materials | en |
dc.identifier.rssuri | http://link.aip.org/link/doi/10.1117/12.908916 | en |
dc.contributor.sponsor | Science Foundation Ireland (SFI) | en |
dc.contributor.sponsorGrantNumber | 08/IN.1/I2112 | en |