Iterative machine learning based rotational alignment of brain 3D CT data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU132791" target="_blank" >RIV/00216305:26220/19:PU132791 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8857858" target="_blank" >https://ieeexplore.ieee.org/document/8857858</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EMBC.2019.8857858" target="_blank" >10.1109/EMBC.2019.8857858</a>
Alternative languages
Result language
angličtina
Original language name
Iterative machine learning based rotational alignment of brain 3D CT data
Original language description
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).
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20601 - Medical engineering
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2019 41th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
ISBN
978-1-5386-1312-2
ISSN
1557-170X
e-ISSN
—
Number of pages
5
Pages from-to
4404-4408
Publisher name
IEEE
Place of publication
Berlin, Germany
Event location
Berlin
Event date
Jul 23, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000557295304193