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Using grey-level and shape information for decomposing proteins in 3D images
Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2004 (English)In: IEEE International, 2004, p. 800-803Conference paper, Published paper (Refereed)
Abstract [en]

An image analysis method for decomposing 3D objects using a combination

of grey-level and shape is presented. The method consists of two major p

arts: seeding based on grey-level information and growth from the seeds

based on shape information. The growth is performed in two steps in orde

r to prevent seeds located in peripheral or protruding parts of the obje

ct from growing into other parts. The method was developed to decompose

3D reconstructions of proteins into their structural subunits. The prote

ins are imaged with SET (Sidec Electron Tomography) at a resolution of a

pproximately 2nm, and delineated from the background by thresholding pri

or to application of our decomposition method. Decomposition can be a us

eful tool in the second step of the segmentation process to help disting

uish between true protein molecules and other objects. It can also be us

eful for analyzing and visualizing interactions between proteins.

Place, publisher, year, edition, pages
2004. p. 800-803
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-67398OAI: oai:DiVA.org:uu-67398DiVA, id: diva2:95309
Available from: 2005-05-23 Created: 2005-05-23 Last updated: 2018-01-10

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Sintorn, Ida-Maria

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