Automatic Particle Picking Algorithms for High Resolution Single Particle Analysis
Banks, Jasmine E., Pailthorpe, Bernard, Rothnagel, Rosalba, & Hankamer, Ben (2005) Automatic Particle Picking Algorithms for High Resolution Single Particle Analysis. In Lovell, Brian C. & Maeder, Anthony J. (Eds.) Australian Pattern Recognition Conference in Digital Image Computing, 21 February 2005, Brisbane.
As new genome sequencing initiatives are completed, one of the next great challenges of cell biology is the atomic resolution structure determination of the enormous number
of proteins they encode. Single particle analysis is a technique which produces 3D structures by computationally aligning high resolution electron microscope images of individual, randomly oriented molecules. One of the limiting factors in producing a high resolution 3D reconstruction is obtaining a large enough representative dataset (~100,000
particles). Traditionally particles have been picked manually but this is a slow and labour intensive process. This paper describes two automatic particle picking algorithms,
based on correlation and edge detection, which have been shown to be capable of quickly selecting a large number of particles in micrographs. Currently circular and rectangular particles are able to be picked.
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|Item Type:||Conference Paper|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
|Copyright Owner:||The Australian Pattern Recognition Society|
|Copyright Statement:||The conference proceedings are freely accessible online via the association's web page (see hypertext link).|
|Deposited On:||09 May 2007|
|Last Modified:||29 Feb 2012 23:19|
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