Development of a Convolutional Neural Network Based Skull Segmentation in MRI Using Standard Tesselation Language Models.
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ABSTRACT:
SUBMITTER: Dalvit Carvalho da Silva R
PROVIDER: S-EPMC8074044 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Publications
Development of a Convolutional Neural Network Based Skull Segmentation in MRI Using Standard Tesselation Language Models.
Dalvit Carvalho da Silva Rodrigo R Jenkyn Thomas Richard TR Carranza Victor Alexander VA
Journal of personalized medicine 20210416 4
Segmentation is crucial in medical imaging analysis to help extract regions of interest (ROI) from different imaging modalities. The aim of this study is to develop and train a 3D convolutional neural network (CNN) for skull segmentation in magnetic resonance imaging (MRI). 58 gold standard volumetric labels were created from computed tomography (CT) scans in standard tessellation language (STL) models. These STL models were converted into matrices and overlapped on the 58 corresponding MR image ...[more]
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