<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Manual analysis of brain tumors magnetic resonance images is usually accompanied by some problem. Several techniques have been proposed for the brain tumor segmentation. This study will be focused on searching popular databases for related studies, theoretical and practical aspects of Convolutional Neural Network surveyed in brain tumor segmentation. Based on our findings, details about related studies including the datasets used, evaluation parameters, preferred architectures and complementary steps analyzed. Deep learning as a revolutionary idea in image processing, achieved brilliant results in brain tumor segmentation too. This can be continuing until the next revolutionary idea emerging.</p></abstract>

Manual analysis of brain tumors magnetic resonance images is usually accompanied by some problem. Several techniques have been proposed for the brain tumor segmentation. This study will be focused on searching popular databases for related studies, theoretical and practical aspects of Convolutional Neural Network surveyed in brain tumor segmentation. Based on our findings, details about related studies including the datasets used, evaluation parameters, preferred architectures and complementary steps analyzed. Deep learning as a revolutionary idea in image processing, achieved brilliant results in brain tumor segmentation too. This can be continuing until the next revolutionary idea emerging.

Emergence of Convolutional Neural Network in Future Medicine: Why and How. A Review on Brain Tumor Segmentation

Shahid Beheshti University of Medical Sciences

Health Information Technology and Management department, Faculty of Paramedical Sciences

Brain and Spinal Cord Injury Research Center, Neuroscience Institute

Department of Neurosurgery, Shariati Hospital

Department of Radiology, Hazrat Rasoul Akram Hospital, School of Medicine

Polish Journal of Medical Physics and Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Manual analysis of brain tumors magnetic resonance images is usually accompanied by some problem. Several techniques have been proposed for the brain tumor...

Emergence of Convolutional Neural Network in Future Medicine: Why and How. A Review on Brain Tumor Segmentation

Published Online: Apr 04, 2018

Page range: 43 - 53

Received: Oct 31, 2017

Accepted: Feb 01, 2018

DOI: https://doi.org/10.2478/pjmpe-2018-0007

Keywords
convolution neural network, brain tumor, segmentation, deep learning

© 2018 Behrouz Alizadeh Savareh et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Emergence of Convolutional Neural Network in Future Medicine: Why and How. A Review on Brain Tumor Segmentation

Published Online: Apr 04, 2018

Page range: 43 - 53

Received: Oct 31, 2017

Accepted: Feb 01, 2018

DOI: https://doi.org/10.2478/pjmpe-2018-0007

Keywordsconvolution neural network, brain tumor, segmentation, deep learning

© 2018 Behrouz Alizadeh Savareh et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
convolution neural network, brain tumor, segmentation, deep learning