xiaojiean815/exapp

Learning Expected Appearances for Intraoperative Medical Registration

Expected Appearances

Learning Expected Appearances for Intraoperative Registration

This repository contains the python source code for the paper: Learning Expected Appearances for Intraoperative Registration: Application to Neurosurgical Guidance. To appear in MICCAI 2023.

Dataset

Synthesized images and 3D poses can be downloaded here: Google Drive Dataset

Prerequisites

• python
• sklearn
• skimage
• numpy
• elasticdeform
• pickle
• opencv
• tensorFlow/keras

Neural Style Transfer

The neural style transfer function is based on this code: Online Neural Doodle

Citation

If you use this code or data for your research please cite this paper.

@ARTICLE{haouchine2023exapp,
author = {Haouchine, Nazim and Dorent, Reuben and Juvekar, Parikshit and Torio, Erikcson and Wells III, William and Kapur, Tina and Golby, Alexandra and Frisken, Sarah},
year = {2023},
month = {-},
journal={International Conference on Medical Image Computing and Computer-Assisted Intervention. MICCAI 2023},
pages = {-},
title = {Learning Expected Appearances for Intraoperative Registration: Application to Neurosurgical Guidance},
volume = {-},
isbn = {-}
}