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  Fast segmentation of brain magnetic resonance tomograms

Mittelhäußer, G., & Kruggel, F. J. (1995). Fast segmentation of brain magnetic resonance tomograms. In N. Ayache (Ed.), Computer vision, virtual reality and robotics in medicine (pp. 237-241). Berlin: Springer.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-3AF8-5 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-3AF9-4
Genre: Conference Paper

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 Creators:
Mittelhäußer, Gangolf1, Author
Kruggel, Frithjof J.1, Author              
Affiliations:
1External Organizations, ou_persistent22              

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Free keywords: White Matter; Basal Ganglion; Segment Model; Gradient Magnitude; Neighboring Segment
 Abstract: We describe a combination of a region growing and a watershed algorithm optimized for the detection of homogeneous structures in magnetic resonance (MR) volume datasets. No prior knowledge is used except a segment model. The adaptation to different data sets is controlled by parameters which can be determined interactively due to the high speed of the algorithm. Results are shown for the segmentation of the basal ganglia and the white matter of the brain.

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Language(s): eng - English
 Dates: 1995-04-26
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/978-3-540-49197-2_27
 Degree: -

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Title: First International Conference, VCRMed'95
Place of Event: Nice, France
Start-/End Date: 1995-04-03 - 1995-04-06

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Source 1

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Title: Computer vision, virtual reality and robotics in medicine
Source Genre: Proceedings
 Creator(s):
Ayache, Nicholas1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 237 - 241 Identifier: ISBN: 3-540-59120-6

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Title: Lecture Notes in Computer Science
  Other : Lect. Notes Comput. Sci.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: 905 Sequence Number: - Start / End Page: - Identifier: ISSN: 0302-9743
CoNE: https://pure.mpg.de/cone/journals/resource/954928560451