Deep learning meets topology-preserving active contours: towards scalable quantitative histology of cortical cytoarchitecture.

K. Thierbach; P.L. Bazin; F. Gavriilidis; E. Kirilina; C. Jager; M. Morawski; S. Geyer; Nikolaus Weiskopf; N. Scherf

Deep learning meets topology-preserving active contours: towards scalable quantitative histology of cortical cytoarchitecture.

K. Thierbach
, P.L. Bazin
, F. Gavriilidis
, E. Kirilina
, C. Jager
, M. Morawski
, S. Geyer
, Nikolaus Weiskopf
, N. Scherf

NIN

Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgave › Artikel › Wetenschappelijk › peer review

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Originele taal-2	Engels
Tijdschrift	bioRxiv
Status	E-pub ahead of print - 2019

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Thierbach2018bioRxivFinal published version, 1,5 MB

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title = "Deep learning meets topology-preserving active contours: towards scalable quantitative histology of cortical cytoarchitecture.",

author = "K. Thierbach and P.L. Bazin and F. Gavriilidis and E. Kirilina and C. Jager and M. Morawski and S. Geyer and Nikolaus Weiskopf and N. Scherf",

year = "2019",

language = "English",

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AU - Thierbach, K.

AU - Bazin, P.L.

AU - Gavriilidis, F.

AU - Kirilina, E.

AU - Jager, C.

AU - Morawski, M.

AU - Geyer, S.

AU - Weiskopf, Nikolaus

AU - Scherf, N.

PY - 2019

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M3 - Article

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