Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI Scans
Brain tumors are nonlinear and present with variations in their size, form, and textural variation; this might make it difficult to diagnose them and perform surgical excision using magnetic resonance imaging (MRI) scans. The procedures that are currently available are conducted by radiologists, bra...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/13/7/1229 |
| _version_ | 1827747006520492032 |
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| author | Farah Mohammad Saad Al Ahmadi Jalal Al Muhtadi |
| author_facet | Farah Mohammad Saad Al Ahmadi Jalal Al Muhtadi |
| author_sort | Farah Mohammad |
| collection | DOAJ |
| description | Brain tumors are nonlinear and present with variations in their size, form, and textural variation; this might make it difficult to diagnose them and perform surgical excision using magnetic resonance imaging (MRI) scans. The procedures that are currently available are conducted by radiologists, brain surgeons, and clinical specialists. Studying brain MRIs is laborious, error-prone, and time-consuming, but they nonetheless show high positional accuracy in the case of brain cells. The proposed convolutional neural network model, an existing blockchain-based method, is used to secure the network for the precise prediction of brain tumors, such as pituitary tumors, meningioma tumors, and glioma tumors. MRI scans of the brain are first put into pre-trained deep models after being normalized in a fixed dimension. These structures are altered at each layer, increasing their security and safety. To guard against potential layer deletions, modification attacks, and tempering, each layer has an additional block that stores specific information. Multiple blocks are used to store information, including blocks related to each layer, cloud ledger blocks kept in cloud storage, and ledger blocks connected to the network. Later, the features are retrieved, merged, and optimized utilizing a Genetic Algorithm and have attained a competitive performance compared with the state-of-the-art (SOTA) methods using different ML classifiers. |
| first_indexed | 2024-03-11T05:40:01Z |
| format | Article |
| id | doaj.art-953ee497946d44de96bbd68960523d7e |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-11T05:40:01Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-953ee497946d44de96bbd68960523d7e2023-11-17T16:29:37ZengMDPI AGDiagnostics2075-44182023-03-01137122910.3390/diagnostics13071229Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI ScansFarah Mohammad0Saad Al Ahmadi1Jalal Al Muhtadi2Center of Excellence in Information Assurance (CoEIA), King Saud University, Riyadh 11543, Saudi ArabiaCollege of Computer & Information Sciences, King Saud University, Riyadh 11543, Saudi ArabiaCenter of Excellence in Information Assurance (CoEIA), King Saud University, Riyadh 11543, Saudi ArabiaBrain tumors are nonlinear and present with variations in their size, form, and textural variation; this might make it difficult to diagnose them and perform surgical excision using magnetic resonance imaging (MRI) scans. The procedures that are currently available are conducted by radiologists, brain surgeons, and clinical specialists. Studying brain MRIs is laborious, error-prone, and time-consuming, but they nonetheless show high positional accuracy in the case of brain cells. The proposed convolutional neural network model, an existing blockchain-based method, is used to secure the network for the precise prediction of brain tumors, such as pituitary tumors, meningioma tumors, and glioma tumors. MRI scans of the brain are first put into pre-trained deep models after being normalized in a fixed dimension. These structures are altered at each layer, increasing their security and safety. To guard against potential layer deletions, modification attacks, and tempering, each layer has an additional block that stores specific information. Multiple blocks are used to store information, including blocks related to each layer, cloud ledger blocks kept in cloud storage, and ledger blocks connected to the network. Later, the features are retrieved, merged, and optimized utilizing a Genetic Algorithm and have attained a competitive performance compared with the state-of-the-art (SOTA) methods using different ML classifiers.https://www.mdpi.com/2075-4418/13/7/1229brain tumordeep learningblockchainsecure CNN |
| spellingShingle | Farah Mohammad Saad Al Ahmadi Jalal Al Muhtadi Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI Scans Diagnostics brain tumor deep learning blockchain secure CNN |
| title | Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI Scans |
| title_full | Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI Scans |
| title_fullStr | Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI Scans |
| title_full_unstemmed | Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI Scans |
| title_short | Blockchain-Based Deep CNN for Brain Tumor Prediction Using MRI Scans |
| title_sort | blockchain based deep cnn for brain tumor prediction using mri scans |
| topic | brain tumor deep learning blockchain secure CNN |
| url | https://www.mdpi.com/2075-4418/13/7/1229 |
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