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ORCIDAutoImplant@MICCAI 2021, Strasbourg, France
- Jianning Li
, Jan Egger:
Towards the Automatization of Cranial Implant Design in Cranioplasty II - Second Challenge, AutoImplant 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings. Lecture Notes in Computer Science 13123, Springer 2021, ISBN 978-3-030-92651-9 - Laurèl Rauschenbach, Christoph Rieß, Ulrich Sure, Karsten H. Wrede:
Personalized Calvarial Reconstruction in Neurosurgery. 1-7 - David G. Ellis, Carlos M. Alvarez, Michele R. Aizenberg:
Qualitative Criteria for Feasible Cranial Implant Designs. 8-18 - Oldrich Kodym, Michal Spanel, Adam Herout:
Segmentation of Defective Skulls from CT Data for Tissue Modelling. 19-28 - Marek Wodzinski, Mateusz Daniol, Daria Hemmerling:
Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets. 29-44 - Jianning Li, Antonio Pepe, Christina Gsaxner, Yuan Jin, Jan Egger:
Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation. 45-62 - Hamza Mahdi, Allison Clement, Evan Kim, Zachary Fishman, Cari M. Whyne, James G. Mainprize, Michael R. Hardisty:
A U-Net Based System for Cranial Implant Design with Pre-processing and Learned Implant Filtering. 63-79 - Artem Kroviakov, Jianning Li, Jan Egger:
Sparse Convolutional Neural Network for Skull Reconstruction. 80-94 - Bokai Yang, Ke Fang, Xingyu Li:
Cranial Implant Prediction by Learning an Ensemble of Slice-Based Skull Completion Networks. 95-104 - Lei Yu, Jianning Li, Jan Egger:
PCA-Skull: 3D Skull Shape Modelling Using Principal Component Analysis. 105-115 - Shashwat Pathak, Chitimireddy Sindhura, Rama Krishna Sai Subrahmanyam Gorthi, Degala Venkata Kiran, Subrahmanyam Gorthi:
Cranial Implant Design Using V-Net Based Region of Interest Reconstruction. 116-128
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