@conference{Less19c,
title = {Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network},
author = {Nikolas Lessmann, Jelmer M. Wolterink, Majd Zreik, Max A. Viergever, Bram van Ginneken, Ivana Išgum},
url = {https://openreview.net/forum?id=B1eQv5INqV},
year = {2019},
date = {2019-07-08},
booktitle = {Medical Imaging with Deep Learning. MIDL London},
abstract = {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 dened 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.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}