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arXiv Open Access 2019

Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network

Nikolas Lessmann Jelmer M. Wolterink Majd Zreik Max A. Viergever Bram van Ginneken +1 lainnya
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Abstrak

Thin-plate splines can be used for interpolation of image values, but can also be used to represent a smooth surface, such as the boundary between two structures. We present a method for partitioning vertebra segmentation masks into two substructures, the vertebral body and the posterior elements, using a convolutional neural network that predicts the boundary between the two structures. This boundary is modeled as a thin-plate spline surface defined by a set of control points predicted by the network. The neural network is trained using the reconstruction error of a convolutional autoencoder to enable the use of unpaired data.

Topik & Kata Kunci

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Penulis (6)

N

Nikolas Lessmann

J

Jelmer M. Wolterink

M

Majd Zreik

M

Max A. Viergever

B

Bram van Ginneken

I

Ivana Išgum

Format Sitasi

APA MLA BibTeX
Lessmann, N., Wolterink, J.M., Zreik, M., Viergever, M.A., Ginneken, B.v., Išgum, I. (2019). Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network. https://arxiv.org/abs/1907.10978

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Informasi Jurnal
Tahun Terbit
2019
Bahasa
en
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arXiv
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Open Access ✓