Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share By
Emergence of Convolutional Neural Network in Future Medicine: Why and How. a Review on Brain Tumor Segmentation Publisher



Alizadeh Savareh B1 ; Emami H2 ; Hajiabadi M3, 4 ; Ghafoori M5 ; Majid Azimi S6
Authors

Source: Polish Journal of Medical Physics and Engineering Published:2018


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. © 2018 Behrouz Alizadeh Savareh et al., published by De Gruyter Open.
Related Docs
View other Related Docs
1. Wavelet-Enhanced Convolutional Neural Network: A New Idea in a Deep Learning Paradigm, Biomedizinische Technik (2019)
2. Comparison of Wavelet Transformations to Enhance Convolutional Neural Network Performance in Brain Tumor Segmentation, BMC Medical Informatics and Decision Making (2021)
3. Brain Tumor Segmentation Using Hierarchical Combination of Fuzzy Logic and Cellular Automata, Journal of Medical Signals and Sensors (2022)
Experts (# of related papers)
View all Related Experts
Alireza Ahmadian (4)
Seyed Maysam Alimohamadi (2)
Other Related Docs
4. Fully Automated Clinical Target Volume Segmentation for Glioblastoma Radiotherapy Using a Deep Convolutional Neural Network, Polish Journal of Radiology (2023)
5. Mri-Based Brain Tumor Detection Using Convolutional Deep Learning Methods and Chosen Machine Learning Techniques, BMC Medical Informatics and Decision Making (2023)
6. Brain Tumor Segmentation Using Multimodal Mri and Convolutional Neural Network, 2022 30th International Conference on Electrical Engineering# ICEE 2022 (2022)
7. Segmentation of Pancreatic Ductal Adenocarcinoma (Pdac) and Surrounding Vessels in Ct Images Using Deep Convolutional Neural Networks and Texture Descriptors, Scientific Reports (2022)
8. Accurate Automatic Glioma Segmentation in Brain Mri Images Based on Capsnet, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society# EMBS (2021)
9. Deep Learning-Based Automated Delineation of Head and Neck Malignant Lesions From Pet Images, 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference# NSS/MIC 2020 (2020)
10. An Improved Capsule Network for Glioma Segmentation on Mri Images: A Curriculum Learning Approach, Computers in Biology and Medicine (2022)
11. Fully Automated Gross Tumor Volume Delineation From Pet in Head and Neck Cancer Using Deep Learning Algorithms, Clinical Nuclear Medicine (2021)
12. Computer-Aided Detection (Cade) and Segmentation Methods for Breast Cancer Using Magnetic Resonance Imaging (Mri), Journal of Magnetic Resonance Imaging (2025)
13. Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric Mri: A Review on Clinical Applications and Future Outlooks, Journal of Magnetic Resonance Imaging (2025)
14. Current Trends in Glioma Tumor Segmentation: A Survey of Deep Learning Modules, Physica Medica (2025)
15. Segmentation of Gbm in Mri Images Using an Efficient Speed Function Based on Level Set Method, Proceedings - 2017 10th International Congress on Image and Signal Processing# BioMedical Engineering and Informatics# CISP-BMEI 2017 (2017)
16. Deep Learning Techniques and Covid-19 Drug Discovery: Fundamentals, State-Of-The-Art and Future Directions, Studies in Systems# Decision and Control (2021)
17. Microcalcification Detection in Mammograms Using Deep Learning, Iranian Journal of Radiology (2022)
18. Deep Learning-Based Techniques for Estimating High-Quality Full-Dose Positron Emission Tomography Images From Low-Dose Scans: A Systematic Review, BMC Medical Imaging (2024)
19. Automated Deep Identification of Radiopharmaceutical Type and Body Region From Pet Images, Iranian Journal of Nuclear Medicine (2024)
20. Deep Learning Techniques for Cervical Cancer Diagnosis Based on Pathology and Colposcopy Images, Informatics in Medicine Unlocked (2024)