The University of Dublin | Trinity College -- Ollscoil Átha Cliath | Coláiste na Tríonóide
Trinity's Access to Research Archive
Home :: Log In :: Submit :: Alerts ::

School of Engineering >
Electronic & Electrical Eng >
Electronic & Electrical Eng (Scholarly Publications) >

Please use this identifier to cite or link to this item:

Title: A wavelet-based Bayesian framework for 3D object segmentation in microscopy
Name Grant Number

Author's Homepage:
Keywords: Microscopy
3-D objects
Issue Date: 2012
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
Series/Report no.: Proceedings of SPIE
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.
Description: PUBLISHED
Related links:
Appears in Collections:Electronic & Electrical Eng (Scholarly Publications)

Files in This Item:

File Description SizeFormat
A Wavelet-Based Bayesian Framework for 3D Object Segmentation in Microscopy.pdfPublished (publisher's copy) - Peer Reviewed5.88 MBAdobe PDFView/Open

This item is protected by original copyright

Please note: There is a known bug in some browsers that causes an error when a user tries to view large pdf file within the browser window. If you receive the message "The file is damaged and could not be repaired", please try one of the solutions linked below based on the browser you are using.

Items in TARA are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback