A ridge-based framework for segmentation of 3D electron microscopy datasets

Martinez-Sanchez, Antonio; García, Inmaculada; Fernández, Jose-Jesús

Publication:
A ridge-based framework for segmentation of 3D electron microscopy datasets

dc.contributor.author	Martinez-Sanchez, Antonio
dc.contributor.author	García, Inmaculada
dc.contributor.author	Fernández, Jose-Jesús
dc.contributor.department	Ingeniería de la Información y las Comunicaciones
dc.date.accessioned	2023-11-30T07:43:23Z
dc.date.available	2023-11-30T07:43:23Z
dc.date.issued	2013-01
dc.description	© 2013. Elsevier. This document is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Accepted version of a Published Work that appeared in final form in Journal of Structural Biology. To access the final edited and published work see https://doi.org/10.1016/j.jsb.2012.10.002	es
dc.description.abstract	Three-dimensional (3D) electron microscopy (EM) has become a major player in structural cell biology as it enables the analysis of subcellular architecture at an unprecedented level of detail. Interpretation of the resulting 3D volumes strongly depends on segmentation, which consists in decomposing the volume into their structural components. The computational approaches proposed so far have not turned out to be of general applicability. Thus, manual segmentation still remains a prevalent method. Here, a new computational framework for segmentation of 3D EM datasets is introduced. It relies on detection and characterization of ridges (i.e. local maxima). The detected ridges are modelled as asymmetric Gaussian functions whose parameters constitute ridge descriptors. This local information is then used to cluster the ridges, which leads to the ultimate segmentation. In this work we focus on membranes and locally planar structures in general. The performance of the framework is illustrated with its application to a number of complex 3D datasets and a quantitative analysis.	es
dc.format	application/pdf	es
dc.format.extent	41	es
dc.identifier.doi	https://doi.org/10.1016/j.jsb.2012.10.002
dc.identifier.eisbn	Journal of Structural Biology Vol. 181, Issue 1, January 2013, Pages 61-70	es
dc.identifier.issn	1047-8477
dc.identifier.uri	http://hdl.handle.net/10201/136243
dc.language	eng	es
dc.publisher	Elsevier	es
dc.relation	This work has been partially supported by the Spanish Ministry of Science (TIN2008-01117, TIN2012-37483), J. Andalucia (P10-TIC-6002, P11-TIC-7176), in part thanks to European Reg. Dev. Funds (ERDF). A.M.S. is a fellow of the Spanish FPI programme.	es
dc.rights	info:eu-repo/semantics/openAccess	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	Segmentation	es
dc.subject	Image Processing	es
dc.subject	Electron Tomography	es
dc.subject	Serial section 3D Reconstruction	es
dc.subject	Serial Blockface	es
dc.subject	Membrane	es
dc.title	A ridge-based framework for segmentation of 3D electron microscopy datasets	es
dc.type	info:eu-repo/semantics/article	es
dspace.entity.type	Publication	es