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

Jianning Li, Jan Egger (Herausgeber)

Buch | Softcover
IX, 129 Seiten
2021 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-92651-9 (ISBN)
58,84 inkl. MwSt

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.

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.

Erscheinungsdatum
Reihe/Serie Image Processing, Computer Vision, Pattern Recognition, and Graphics
Lecture Notes in Computer Science
Zusatzinfo IX, 129 p. 76 illus., 67 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 226 g
Themenwelt Schulbuch / Wörterbuch Unterrichtsvorbereitung Unterrichts-Handreichungen
Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Artificial Intelligence • Bioinformatics • Computer Networks • Computer systems • computer vision • cranial implant design • craniectomy • cranioplasty • Craniotomy • Deep learning • Image Analysis • image enhancement • Image Processing • image reconstruction • Image Segmentation • machine learning • Medical Images • Neural networks • pattern recognition • reconstruction • shape completion • shape prior • skull reconstruction • statistical shape model
ISBN-10 3-030-92651-6 / 3030926516
ISBN-13 978-3-030-92651-9 / 9783030926519
Zustand Neuware
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