Semi-automated segmentation of pre-operative low grade gliomas in magnetic resonance imaging
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F15%3A10297781" target="_blank" >RIV/00216208:11110/15:10297781 - isvavai.cz</a>
Alternative codes found
RIV/61383082:_____/15:#0000361 RIV/00159816:_____/15:00063200
Result on the web
<a href="http://dx.doi.org/10.1186/s40644-015-0047-z" target="_blank" >http://dx.doi.org/10.1186/s40644-015-0047-z</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1186/s40644-015-0047-z" target="_blank" >10.1186/s40644-015-0047-z</a>
Alternative languages
Result language
angličtina
Original language name
Semi-automated segmentation of pre-operative low grade gliomas in magnetic resonance imaging
Original language description
Segmentation of pre-operative low-grade gliomas (LGGs) from magnetic resonance imaging is a crucial step for studying imaging biomarkers. However, segmentation of LGGs is particularly challenging because they rarely enhance after gadolinium administration. Like other gliomas, they have irregular tumor shape, heterogeneous composition, ill-defined tumor boundaries, and limited number of image types. To overcome these challenges we propose a semi-automated segmentation method that relies only on T2-weighted (T2W) and optionally post-contrast T1-weighted (T1W) images. First, the user draws a region-of-interest (ROI) that completely encloses the tumor and some normal tissue. Second, a normal brain atlas and post-contrast T1W images are registered to T2W images. Third, the posterior probability of each pixel/voxel belonging to normal and abnormal tissues is calculated based on information derived from the atlas and ROI. Finally, geodesic active contours use the probability map of the tumor
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
FD - Oncology and haematology
OECD FORD branch
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Result continuities
Project
<a href="/en/project/ED1.100%2F02%2F0123" target="_blank" >ED1.100/02/0123: St. Anne´s University Hospital Brno - International Clinical Research Center (FNUSA-ICRC)</a><br>
Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Cancer Imaging
ISSN
1470-7330
e-ISSN
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Volume of the periodical
15
Issue of the periodical within the volume
August
Country of publishing house
GB - UNITED KINGDOM
Number of pages
10
Pages from-to
1-10
UT code for WoS article
000359640700001
EID of the result in the Scopus database
2-s2.0-84938915776