Automated macromolecular crystal detection system and method
Abstract
An automated macromolecular method and system for detecting crystals in two-dimensional images, such as light microscopy images obtained from an array of crystallization screens. Edges are detected from the images by identifying local maxima of a phase congruency-based function associated with each image. The detected edges are segmented into discrete line segments, which are subsequently geometrically evaluated with respect to each other to identify any crystal-like qualities such as, for example, parallel lines, facing each other, similarity in length, and relative proximity. And from the evaluation a determination is made as to whether crystals are present in each image.
- Inventors:
-
- Tracy, CA
- San Ramon, CA
- Livermore, CA
- Fontainebleau, FR
- Issue Date:
- Research Org.:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 909579
- Patent Number(s):
- 7227983
- Application Number:
- 10/452,668
- Assignee:
- The Regents of the University of California (Oakland, CA)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06K - RECOGNITION OF DATA
- DOE Contract Number:
- W-7405-ENG-48
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 47 OTHER INSTRUMENTATION
Citation Formats
Christian, Allen T, Segelke, Brent, Rupp, Bernard, and Toppani, Dominique. Automated macromolecular crystal detection system and method. United States: N. p., 2007.
Web.
Christian, Allen T, Segelke, Brent, Rupp, Bernard, & Toppani, Dominique. Automated macromolecular crystal detection system and method. United States.
Christian, Allen T, Segelke, Brent, Rupp, Bernard, and Toppani, Dominique. Tue .
"Automated macromolecular crystal detection system and method". United States. https://www.osti.gov/servlets/purl/909579.
@article{osti_909579,
title = {Automated macromolecular crystal detection system and method},
author = {Christian, Allen T and Segelke, Brent and Rupp, Bernard and Toppani, Dominique},
abstractNote = {An automated macromolecular method and system for detecting crystals in two-dimensional images, such as light microscopy images obtained from an array of crystallization screens. Edges are detected from the images by identifying local maxima of a phase congruency-based function associated with each image. The detected edges are segmented into discrete line segments, which are subsequently geometrically evaluated with respect to each other to identify any crystal-like qualities such as, for example, parallel lines, facing each other, similarity in length, and relative proximity. And from the evaluation a determination is made as to whether crystals are present in each image.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2007},
month = {6}
}
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