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

Research output: Contribution to journal/periodical › Article › Scientific › peer-review

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Original language	English
Journal	bioRxiv
Publication status	E-pub ahead of print - 2019

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Thierbach, K., Bazin, P. L., Gavriilidis, F., Kirilina, E., Jager, C., Morawski, M., Geyer, S., Weiskopf, N., & Scherf, N. (2019). Deep learning meets topology-preserving active contours: towards scalable quantitative histology of cortical cytoarchitecture. bioRxiv.

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AU - Jager, C.

AU - Morawski, M.

AU - Geyer, S.

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AU - Scherf, N.

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