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

by Jianning Li (Editor), Jan Egger (Editor)

Overview

This book constitutes the Second Automatization of Cranial Implant Design in Cranioplasty Challenge, AutoImplant 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September, 2021. The challenge took place virtually due to the COVID-19 pandemic.

The 7 papers are presented together with one invited paper, one qualitative evaluation criteria from neurosurgeons and a dataset descriptor. This challenge aims to provide more affordable, faster, and more patient-friendly solutions to the design and manufacturing of medical implants, including cranial implants, which is needed in order to repair a defective skull from a brain tumor surgery or trauma. The presented solutions can serve as a good benchmark for future publications regarding 3D volumetric shape learning and cranial implant design.

Product Details

ISBN-13:	9783030926526
Publisher:	Springer-Verlag New York, LLC
Publication date:	12/02/2021
Series:	Lecture Notes in Computer Science , #13123
Sold by:	Barnes & Noble
Format:	eBook
File size:	34 MB
Note:	This product may take a few minutes to download.

Table of Contents

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.