Segmentation Of Brain Tumor Based On Mri USING CONVOLUTIONAL NEURAL NETWORKS
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- Englisch ausgewählt
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Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
05.06.2020
Verlag
LAP LAMBERT Academic PublishingSeitenzahl
64
Maße (L/B/H)
22/15/0.5 cm
Gewicht
113 g
Auflage
1. Auflage
Sprache
Englisch
ISBN
978-620-2-55746-7
Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. Here, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3*3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against over fitting, given the fewer number of weights in the network.
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