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CHMELÍK, J. JAKUBÍČEK, R. VIČAR, T. WALEK, P. OUŘEDNÍČEK, P. JAN, J.
Originální název
Iterative machine learning based rotational alignment of brain 3D CT data
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
The optimal rotational alignment of brain Computed Tomography (CT) images to a required standard position has a crucial importance for both automatic and manual diagnostic analysis. In this contribution, we present a novel two-step iterative approach for the automatic 3D rotational alignment of brain CT data. The angles of axial and coronal rotations are determined by an unsupervised by localisation of the Midsagittal Plane (MSP) method. This includes detection and pairing of medially symmetrical feature points. The sagittal rotation angle is subsequently estimated by regression convolutional neural network (CNN). The proposed methodology has been evaluated on a dataset of CT data manually aligned by radiologists. It has been shown that the algorithm achieved the low error of estimated rotations (1 degree) and in a significantly shorter time than the experts (2 minutes per case).
Klíčová slova
CT; brain; alignement; machine learning
Autoři
CHMELÍK, J.; JAKUBÍČEK, R.; VIČAR, T.; WALEK, P.; OUŘEDNÍČEK, P.; JAN, J.
Vydáno
7. 10. 2019
Nakladatel
IEEE
Místo
Berlin, Germany
ISBN
978-1-5386-1312-2
Kniha
2019 41th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Číslo edice
19
ISSN
1557-170X
Periodikum
Proceedings IEEE EMBC
Ročník
Stát
Spojené státy americké
Strany od
4404
Strany do
4408
Strany počet
5
URL
https://ieeexplore.ieee.org/document/8857858
BibTex
@inproceedings{BUT157792, author="Jiří {Chmelík} and Roman {Jakubíček} and Tomáš {Vičar} and Petr {Walek} and Petr {Ouředníček} and Jiří {Jan}", title="Iterative machine learning based rotational alignment of brain 3D CT data", booktitle="2019 41th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)", year="2019", journal="Proceedings IEEE EMBC", volume="19", number="19", pages="4404--4408", publisher="IEEE", address="Berlin, Germany", doi="10.1109/EMBC.2019.8857858", isbn="978-1-5386-1312-2", issn="1557-170X", url="https://ieeexplore.ieee.org/document/8857858" }