Publication Details

Cranial Defect Reconstruction Using Cascaded CNN with Alignment

KODYM, O.; ŠPANĚL, M.; HEROUT, A. Cranial Defect Reconstruction Using Cascaded CNN with Alignment. In Towards the Automatization of Cranial Implant Design in Cranioplasty. Lecture Notes in Computer Science. Lima: Springer Nature Switzerland AG, 2020. p. 56-64. ISBN: 978-3-030-64326-3.
Czech title
Rekonstrukce kraniálních defektů s použitím kaskády CNN se zarovnáním
Type
conference paper
Language
English
Authors
Kodym Oldřich, Ing., Ph.D.
Španěl Michal, doc. Ing., Ph.D. (DCGM)
Herout Adam, prof. Ing., Ph.D. (DCGM)
URL
Keywords

Alingment, Computer aided design, Convolutional neural networks, Deep learnin,
Defects, Medical computing, Statistical tests

Abstract

Designing a patient-specific cranial implant usually requires reconstructing the
defective part of the skull using computer-aided design software, which is
a tedious and time-demanding task. This lead to some recent advances in the field
of automatic skull reconstruction with use of methods based on shape analysis or
deep learning. The AutoImplant Challenge aims at providing a public platform for
benchmarking skull reconstruction methods. The BUT submission to this challenge
is based on skull alignment using landmark detection followed by a cascade of
low-resolution and high-resolution reconstruction convolutional neural network.
We demonstrate that the proposed method successfully reconstructs every skull in
the standard test dataset and outperforms the baseline method in both overlap and
distance metrics, achieving 0.920 DSC and 4.137 mm HD.

Published
2020
Pages
56–64
Proceedings
Towards the Automatization of Cranial Implant Design in Cranioplasty
Series
Lecture Notes in Computer Science
Conference
MICCAI 2020 Cranial Implant Design Challenge, Lima, PE
ISBN
978-3-030-64326-3
Publisher
Springer Nature Switzerland AG
Place
Lima
DOI
UT WoS
000925207100007
EID Scopus
BibTeX
@inproceedings{BUT168486,
  author="Oldřich {Kodym} and Michal {Španěl} and Adam {Herout}",
  title="Cranial Defect Reconstruction Using Cascaded CNN with Alignment",
  booktitle="Towards the Automatization of Cranial Implant Design in Cranioplasty",
  year="2020",
  series="Lecture Notes in Computer Science",
  pages="56--64",
  publisher="Springer Nature Switzerland AG",
  address="Lima",
  doi="10.1007/978-3-030-64327-0\{_}7",
  isbn="978-3-030-64326-3",
  url="https://link.springer.com/chapter/10.1007/978-3-030-64327-0_7"
}
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