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Author Van Eyndhoven, G.; Kurttepeli, M.; van Oers, C.J.; Cool, P.; Bals, S.; Batenburg, K.J.; Sijbers, J. pdf  url
doi  openurl
  Title Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials Type A1 Journal article
  Year (down) 2015 Publication Ultramicroscopy Abbreviated Journal Ultramicroscopy  
  Volume 148 Issue 148 Pages 10-19  
  Keywords A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab; Laboratory of adsorption and catalysis (LADCA)  
  Abstract Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm POre REconstruction and Segmentation is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Amsterdam Editor  
  Language Wos 000345973000002 Publication Date 2014-08-23  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0304-3991; ISBN Additional Links UA library record; WoS full record; WoS citing articles  
  Impact Factor 2.843 Times cited 7 Open Access OpenAccess  
  Notes Colouratom; ECAS_Sara; (ROMEO:green; preprint:; postprint:can ; pdfversion:cannot); Approved Most recent IF: 2.843; 2015 IF: 2.436  
  Call Number c:irua:119083 Serial 2672  
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