Result Details

Segmentation of Defective Skulls from CT Data for Tissue Modelling

KODYM, O.; ŠPANĚL, M.; HEROUT, A. Segmentation of Defective Skulls from CT Data for Tissue Modelling. In Towards the Automatization of Cranial Implant Design in Cranioplasty II. Lecture Notes in Computer Science. Lecture Notes in Computer Science. Strasbourg: Springer Nature Switzerland AG, 2021. no. 13123, p. 19-28. ISBN: 978-3-030-92652-6. ISSN: 0302-9743.
Type
conference paper
Language
English
Authors
Kodym Oldřich, Ing., Ph.D.
Španěl Michal, doc. Ing., Ph.D., DCGM (FIT)
Herout Adam, prof. Ing., Ph.D., DCGM (FIT)
Abstract

This work presents a  method  of  automatic  segmentation of defective skulls for custom cranial implant design and 3D printing  purposes.

Keywords

Computed Tomography, Pre-surgical Planning, Segmentation, Convolutional Neural Networks, Graph-Cut

URL
Published
2021
Pages
19–28
Journal
Lecture Notes in Computer Science, no. 13123, ISSN 0302-9743
Proceedings
Towards the Automatization of Cranial Implant Design in Cranioplasty II
Series
Lecture Notes in Computer Science
Conference
Towards the Automatization of Cranial Implant Design in Cranioplasty: 2nd MICCAI Challenge on Automatic Cranial Implant Design
ISBN
978-3-030-92652-6
Publisher
Springer Nature Switzerland AG
Place
Strasbourg
DOI
10.1007/978-3-030-92652-6_3
UT WoS
000946096000003
EID Scopus
2-s2.0-85121916137
BibTeX 
@inproceedings{BUT187370,
  author="Oldřich {Kodym} and Michal {Španěl} and Adam {Herout}",
  title="Segmentation of Defective Skulls from CT Data for Tissue Modelling",
  booktitle="Towards the Automatization of Cranial Implant Design in Cranioplasty II",
  year="2021",
  series="Lecture Notes in Computer Science",
  journal="Lecture Notes in Computer Science",
  number="13123",
  pages="19--28",
  publisher="Springer Nature Switzerland AG",
  address="Strasbourg",
  doi="10.1007/978-3-030-92652-6\{_}3",
  isbn="978-3-030-92652-6",
  issn="0302-9743",
  url="https://link.springer.com/chapter/10.1007/978-3-030-92652-6_3"
}
Projects
Moderní metody zpracování, analýzy a zobrazování multimediálních a 3D dat, BUT, Vnitřní projekty VUT, FIT-S-20-6460, start: 2020-03-01, end: 2023-02-28, completed
TESCAN 3DIM - Deep learning methods for 3D data analysis, TESCAN 3DIM, start: 2020-01-01, end: 2021-06-30, completed
Research groups
Computer Graphics Research Group (RG GRAPH)
Departments
Department of Computer Graphics and Multimedia (DCGM)
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