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          Institute: MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung)     Collection: Abt. Schölkopf (Empirical Inference)     Display Documents



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ID: 596176.0, MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung) / Abt. Schölkopf (Empirical Inference)
Automatic particle picking using diffusion filtering and random forest classification
Authors:Joubert, P.; Nickell, S.; Beck, F.; Habeck, M.; Hirsch, M.; Schölkopf, B.
Place of Publication:Heidelberg, Germany
Date of Publication (YYYY-MM-DD):2011-09-01
Title of Proceedings:International Workshop on Microscopic Image Analysis with Application in Biology (MIAAB 2011)
Start Page:1
End Page:6
Physical Description:5
Review Status:not specified
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:An automatic particle picking algorithm for processing
electron micrographs of a large molecular complex, the
26S proteasome, is described. The algorithm makes use of a
coherence enhancing diffusion filter to denoise the data, and a random forest classifier for removing false positives. It does not make use of a 3D reference model, but uses a training set of manually picked particles instead. False positive and false negative rates of around 25% to 30% are achieved on a testing set. The algorithm was developed for a specific particle, but contains steps that should be useful for developing automatic picking algorithms for other particles.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Heide Klooz
Affiliations:MPI für Intelligente Systeme/Abt. Schölkopf
Identifiers:URL:http://www.kyb.tuebingen.mpg.de/fileadmin/user_upl...
LOCALID:JoubertNBHHS2011
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