3D Dense-U-Net for MRI brain tissue segmentation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU128515" target="_blank" >RIV/00216305:26220/18:PU128515 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8441508" target="_blank" >https://ieeexplore.ieee.org/document/8441508</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP.2018.8441508" target="_blank" >10.1109/TSP.2018.8441508</a>

Result language
angličtina
Original language name
3D Dense-U-Net for MRI brain tissue segmentation
Original language description
This paper presents a fully automatic method for 3D segmentation of brain tissue on MRI scans using modern deep learning approach and proposes 3D Dense-U-Net neural network architecture using densely connected layers. In contrast with many previous methods, our approach is capable of precise segmentation without any preprocessing of the input image and achieved accuracy 99.70 percent on testing data which outperformed human expert results. The architecture proposed in this paper can also be easily applied to any project already using U-net network as a segmentation algorithm to enhance its results. Implementation was done in Keras on Tensorflow backend and complete source-code was released online.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2018 41st International Conference on Telecommunications and Signal Processing (TSP)
ISBN
978-1-5386-4695-3
ISSN
—
e-ISSN
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Number of pages
4
Pages from-to
237-240
Publisher name
IEEE
Place of publication
Athens, Greece
Event location
Athens, Greece
Event date
Jul 4, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000454845100055

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