Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks

Bálint Antal

2016

Abstract

In this paper, an automatic approach to predict 3D coordinates from stereo laparoscopic images is presented. The approach maps a vector of pixel intensities to 3D coordinates through training a six layer deep neural network. The architectural aspects of the approach is presented and in detail and the method is evaluated on a publicly available dataset with promising results.

References

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Paper Citation


in Harvard Style

Antal B. (2016). Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks . In - SPCS, (PECCS 2016) ISBN , pages 0-0. DOI: 10.5220/0006008001160121


in Bibtex Style

@conference{spcs16,
author={Bálint Antal},
title={Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks},
booktitle={ - SPCS, (PECCS 2016)},
year={2016},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006008001160121},
isbn={},
}


in EndNote Style

TY - CONF
JO - - SPCS, (PECCS 2016)
TI - Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks
SN -
AU - Antal B.
PY - 2016
SP - 0
EP - 0
DO - 10.5220/0006008001160121