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  Development and evaluation of an algorithm for the computer-assisted segmentation of the human hypothalamus on 7-Tesla magnetic resonance images

Schindler, S., Schönknecht, P., Schmidt, L., Anwander, A., Strauß, M., Trampel, R., et al. (2013). Development and evaluation of an algorithm for the computer-assisted segmentation of the human hypothalamus on 7-Tesla magnetic resonance images. PLoS One, 8(7): e66394. doi:10.1371/journal.pone.0066394.

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Schindler_DevelopentEvaluation.pdf (Verlagsversion), 794KB
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Schindler_DevelopentEvaluation.pdf
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2013
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 Urheber:
Schindler, Stephanie1, Autor           
Schönknecht, Peter1, Autor
Schmidt, Laura1, Autor
Anwander, Alfred2, Autor           
Strauß, Maria1, Autor
Trampel, Robert3, Autor           
Bazin, Pierre-Louis3, Autor           
Möller, Harald E.4, Autor           
Hegerl, Ulrich1, Autor
Turner, Robert3, Autor           
Geyer, Stefan3, Autor           
Affiliations:
1Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Germany, ou_persistent22              
2Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
3Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
4Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              

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 Zusammenfassung: Post mortem studies have shown volume changes of the hypothalamus in psychiatric patients. With 7T magnetic resonance imaging this effect can now be investigated in vivo in detail. To benefit from the sub-millimeter resolution requires an improved segmentation procedure. The traditional anatomical landmarks of the hypothalamus were refined using 7T T1-weighted magnetic resonance images. A detailed segmentation algorithm (unilateral hypothalamus) was developed for colour-coded, histogram-matched images, and evaluated in a sample of 10 subjects. Test-retest and inter-rater reliabilities were estimated in terms of intraclass-correlation coefficients (ICC) and Dice’s coefficient (DC). The computer-assisted segmentation algorithm ensured test-retest reliabilities of ICC ≥ .97 (DC ≥ 96.8) and inter-rater reliabilities of ICC ≥ .94 (DC = 95.2). There were no significant volume differences between the segmentation runs, raters, and hemispheres. The estimated volumes of the hypothalamus lie within the range of previous histological and neuroimaging results. We present a computer-assisted algorithm for the manual segmentation of the human hypothalamus using T1-weighted 7T magnetic resonance imaging. Providing very high test-retest and inter-rater reliabilities, it outperforms former procedures established at 1.5T and 3T magnetic resonance images and thus can serve as a gold standard for future automated procedures.

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Sprache(n): eng - English
 Datum: 2013-02-152013-05-072013-07-23
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1371/journal.pone.0066394
PMID: 23935821
PMC: PMC3720799
Anderer: Print 2013
 Art des Abschluß: -

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Titel: PLoS One
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: - Band / Heft: 8 (7) Artikelnummer: e66394 Start- / Endseite: - Identifikator: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850