Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-1097
Main Title: Automatic Segmentation and Skeletonization of Neurons from Confocal Microscope Images based on the 3-D Wavelet Transform
Author(s): Dima, Anca
Scholz, Michael
Obermayer, Klaus
Type: Preprint
Language: English
Language Code: en
Abstract: In this work, we focus on methods for the preprocessing of neurons from three-dimensional (3-D) confocal microscopy images, which are needed for a subsequent detailed morphologic analysis. Due to the specific image properties of confocal microscopy scans, we had to include several heuristic approaches to guarantee meaningful results: 1) a reliable segmentation of objects of different sizes independent of image contrast, and, based on it, 2) the computation of skeleton points along the branch central axes, and 3) the reliable detection of branching points and of problematic regions. These are preprocessing steps to gather information which is needed by the subsequent construction of a graph representing the geometry of the neuron and a final surface reconstruction.
URI: urn:nbn:de:kobv:83-opus-10970
http://depositonce.tu-berlin.de/handle/11303/1394
http://dx.doi.org/10.14279/depositonce-1097
Issue Date: 14-Sep-2005
Date Available: 14-Sep-2005
DDC Class: 004 Datenverarbeitung; Informatik
Subject(s): 3D Neuronale Daten
Confokale Mikroskopie Confocal
Segmentation
3D Multiscale Curvature
3D Neuronal Data
3D-Wavelet Edge Detection
Across-Scales Validation
Branch Detection
Confocal Microscopy
Segmentation
Usage rights: Terms of German Copyright Law
Notes: Revised version published in: IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 11, NO. 7, JULY 2002, S. 790-801
Appears in Collections:Technische Universität Berlin » Fakultäten & Zentralinstitute » Fakultät 4 Elektrotechnik und Informatik » Institut für Softwaretechnik und Theoretische Informatik » Publications

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