Towards the Automatization of Cranial Implant Design in Cranioplasty II

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

Egger, Jan; Li, Jianning

Springer Nature Switzerland AG

12/2021

129

Mole

Inglês

9783030926519

15 a 20 dias

226

Descrição não disponível.
Personalized Calvarial Reconstruction in Neurosurgery.- Qualitative Criteria for Designing Feasible Cranial Implants.- Segmentation of Defective Skulls from CT Data for Tissue Modelling.- Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets.- Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation.- A U-Net based System for Cranial Implant Design with Pre-processing and Learned Implant Filtering.- Sparse Convolutional Neural Network for Skull Reconstruction.- Cranial Implant Prediction by Learning an Ensemble of Slice-based Skull Completion networks.- PCA-Skull: 3D Skull Shape Modelling Using Principal Component Analysis.- Cranial Implant Design using V-Net based Region of Interest Reconstruction.
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artificial intelligence;bioinformatics;computer networks;computer systems;computer vision;deep learning;image analysis;image enhancement;image processing;image reconstruction;image segmentation;machine learning;medical images;neural networks;pattern recognition