| Title: | Automatic Skull Reconstruction |
|---|---|
| Link to paper: | Paper Paper |
| Benchmark: | Skull Reconstruction |
| Link to benchmark dataset: | Download (facial training and test) Download (cranial training) Download (cranial test 1) Download (cranial test 2) Download (cranial test 3 (craniotomy)) |
| Data structure: | voxel occupancy grid |
Methods: Use U-Net style networks that take partial skulls as input and the original skulls as the ground truth
@article{li2021autoimplant,
title={AutoImplant 2020-first MICCAI challenge on automatic cranial implant design},
author={Li, Jianning and Pimentel, Pedro and Szengel, Angelika and Ehlke, Moritz and Lamecker, Hans and Zachow, Stefan and Estacio, Laura and Doenitz, Christian and Ramm, Heiko and Shi, Haochen and others},
journal={IEEE transactions on medical imaging},
volume={40},
number={9},
pages={2329--2342},
year={2021},
publisher={IEEE}
}
@article{li2023towards,
title={Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge},
author={Li, Jianning and Ellis, David G and Kodym, Old{\v{r}}ich and Rauschenbach, Laur{\`e}l and Rie{\ss}, Christoph and Sure, Ulrich and Wrede, Karsten H and Alvarez, Carlos M and Wodzinski, Marek and Daniol, Mateusz and others},
journal={Medical Image Analysis},
pages={102865},
year={2023},
publisher={Elsevier}
}
@inproceedings{li2022training,
title={Training $\beta$-VAE by aggregating a learned Gaussian posterior with a decoupled decoder},
author={Li, Jianning and Fragemann, Jana and Ahmadi, Seyed-Ahmad and Kleesiek, Jens and Egger, Jan},
booktitle={MICCAI Workshop on Medical Applications with Disentanglements},
pages={70--92},
year={2022},
organization={Springer}
}
@article{li2020baseline,
title={MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision},
author={Li, Jianning and Pepe, Antonio and Gsaxner, Christina and others},
journal={arXiv preprint arXiv:2308.16139},
year={2023}
}