Meningioma Detection in MR Images Using Convolutional Neural Network and Computer Vision Methods
Author(s) -
Yulia D. Agafonova,
Andrey Gaidel,
E.N. Surovtsev,
А.V. Kapishnikov
Publication year - 2020
Publication title -
journal of biomedical photonics and engineering
Language(s) - English
Resource type - Journals
ISSN - 2411-2844
DOI - 10.18287/jbpe20.06.030301
Subject(s) - convolutional neural network , artificial intelligence , computer science , segmentation , meningioma , pattern recognition (psychology) , computer vision , artificial neural network , radiology , medicine
The article discusses research efficacy of different architectures of convolutional neural network and methods of computer vision. This paper presents a novel approach to pattern detection of meningioma of the human brain in MR images. MRI images of real patients were made with a help of Samara State Medical University. The result of the research is the automatic procedure of meningioma detection. As a result, post-contrast T1 weighted MRI sequence was the most appropriate for the method based on the baseline statistical segmentation and the diffusion weighted MRI sequence was the most appropriate for the method based on the convolutional neural network. © 2020 Journal of Biomedical Photonics & Engineering.
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