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  Landmark-driven, atlas-based segmentation of mouse brain tissue images containing gene expression data.

Kakadiaris, I., Bello, M., Arunachalam, S., Kang, W., Ju, T., Warren, J., et al. (2004). Landmark-driven, atlas-based segmentation of mouse brain tissue images containing gene expression data. In Medical Image omuting and Computer-Assisted Intervention (pp. 192-199).

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0010-238E-2 Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-0027-C4D9-D
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 Urheber:
Kakadiaris, I., Autor
Bello, M., Autor
Arunachalam, S., Autor
Kang, W., Autor
Ju, T., Autor
Warren, J., Autor
Carson, J., Autor
Chiu, W., Autor
Thaller, C., Autor
Eichele, G.1, Autor           
Affiliations:
1Department of Molecular Embryology, Max Planck Institute for Experimental Endocrinology, Max Planck Society, ou_1565140              

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Schlagwörter: -
 Zusammenfassung: To better understand the development and function of the mammalian brain, researchers have begun to systematically collect a large number of gene expression patterns throughout the mouse brain using technology recently developed for this task. Associating specific gene activity with specific functional locations in the brain anatomy results in a greater understanding of the role of the gene's products. To perform such an association for a large amount of data, reliable automated methods that characterize the distribution of gene expression in relation to a standard anatomical model are required. In this paper, we present an anatomical landmark detection method that has been incorporated into an atlas-based segmentation. The addition of this technique significantly increases the accuracy of automated atlas-deformation. The resulting large-scale annotation will help scientists interpret gene expression patterns more rapidly and accurately.

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Sprache(n): eng - English
 Datum: 2004
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION
 Art der Begutachtung: -
 Identifikatoren: -
 Art des Abschluß: -

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Titel: Medical Image omuting and Computer-Assisted Intervention
Genre der Quelle: Buch
 Urheber:
Barrilot, C., Autor
Haynor, D. L., Autor
Hellier, P., Autor
Affiliations:
-
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 3216 Artikelnummer: - Start- / Endseite: 192 - 199 Identifikator: -