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Title: Automated map sharpening by maximization of detail and connectivity

Abstract

An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures in a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a modelmore » withBfactors (atomic displacement factors; ADPs) set to zero. Finally, this model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.« less

Authors:
 [1];  [2]; ORCiD logo [3];  [4]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); New Mexico Consortium, Los Alamos, NM (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Molecular Biophysics and Integrated Bioimaging Division
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Molecular Biophysics and Integrated Bioimaging Division; Univ. of California, Berkeley, CA (United States). Dept. of Bioengineering
  4. Univ. of California, Berkeley, CA (United States). Dept. of Bioengineering; Shanghai Univ., Shanghai (China). Dept. of Physics and International Centre for Quantum and Molecular Structures
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
National Institutes of Health (NIH); USDOE
OSTI Identifier:
1437712
Alternate Identifier(s):
OSTI ID: 1440481; OSTI ID: 1461163
Report Number(s):
LA-UR-17-30952
Journal ID: ISSN 2059-7983; ACSDAD
Grant/Contract Number:  
AC52-06NA25396; P01GM063210; AC02-05CH11231
Resource Type:
Journal Article: Published Article
Journal Name:
Acta Crystallographica. Section D. Structural Biology
Additional Journal Information:
Journal Volume: 74; Journal Issue: 6; Journal ID: ISSN 2059-7983
Publisher:
IUCr
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 59 BASIC BIOLOGICAL SCIENCES; Biological Science

Citation Formats

Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., and Adams, Paul D. Automated map sharpening by maximization of detail and connectivity. United States: N. p., 2018. Web. doi:10.1107/S2059798318004655.
Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., & Adams, Paul D. Automated map sharpening by maximization of detail and connectivity. United States. doi:10.1107/S2059798318004655.
Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., and Adams, Paul D. Fri . "Automated map sharpening by maximization of detail and connectivity". United States. doi:10.1107/S2059798318004655.
@article{osti_1437712,
title = {Automated map sharpening by maximization of detail and connectivity},
author = {Terwilliger, Thomas C. and Sobolev, Oleg V. and Afonine, Pavel V. and Adams, Paul D.},
abstractNote = {An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures in a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a model withBfactors (atomic displacement factors; ADPs) set to zero. Finally, this model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.},
doi = {10.1107/S2059798318004655},
journal = {Acta Crystallographica. Section D. Structural Biology},
number = 6,
volume = 74,
place = {United States},
year = {Fri May 18 00:00:00 EDT 2018},
month = {Fri May 18 00:00:00 EDT 2018}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1107/S2059798318004655

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Cited by: 4 works
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