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Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

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 Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

 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.


 


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  • Model: PROJ7012
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Monday 29 May, 2017.

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