Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus Optimizer
Classification of medical images plays an indispensable role in medical treatment and training tasks. Much effort and time are required in the extraction and selection of classification features of medical images. Deep Neural Networks (DNNs) are an evolving Machine Learning (ML) method that has prov...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
D. G. Pylarinos
2023-08-01
|
| Series: | Engineering, Technology & Applied Science Research |
| Subjects: | |
| Online Access: | https://etasr.com/index.php/ETASR/article/view/6127 |
| _version_ | 1797745980511092736 |
|---|---|
| author | Thirugnanam Kumar Ramasamy Ponnusamy |
| author_facet | Thirugnanam Kumar Ramasamy Ponnusamy |
| author_sort | Thirugnanam Kumar |
| collection | DOAJ |
| description | Classification of medical images plays an indispensable role in medical treatment and training tasks. Much effort and time are required in the extraction and selection of classification features of medical images. Deep Neural Networks (DNNs) are an evolving Machine Learning (ML) method that has proved its ability in various classification tasks. Convolutional Neural Networks (CNNs) present the optimal results for changing image classification tasks. In this regard, this study focused on developing a Multi-versus Optimizer with Deep Learning Enabled Robust Medical X-ray Image Classification (MVODL-RMXIC) method, aiming to identify abnormalities in medical X-ray images. The MVODL-RMXIC model used the Cross Bilateral Filtering (CBF) technique for noise removal, a MixNet feature extractor with an MVO algorithm based on hyperparameter optimization, and Bidirectional Long-Short-Term Memory (BiLSTM) for image classification. The proposed MVODL-RMXIC model was simulated and evaluated, showing its efficiency over other current methods.
|
| first_indexed | 2024-03-12T15:30:34Z |
| format | Article |
| id | doaj.art-7672bb05b88244198c5daced2655a642 |
| institution | Directory Open Access Journal |
| issn | 2241-4487 1792-8036 |
| language | English |
| last_indexed | 2024-03-12T15:30:34Z |
| publishDate | 2023-08-01 |
| publisher | D. G. Pylarinos |
| record_format | Article |
| series | Engineering, Technology & Applied Science Research |
| spelling | doaj.art-7672bb05b88244198c5daced2655a6422023-08-10T05:33:17ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362023-08-0113410.48084/etasr.6127Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus OptimizerThirugnanam Kumar0Ramasamy Ponnusamy1Department of Computer and Information Science, Annamalai University, IndiaDepartment of Computer and Information Science, Annamalai University, IndiaClassification of medical images plays an indispensable role in medical treatment and training tasks. Much effort and time are required in the extraction and selection of classification features of medical images. Deep Neural Networks (DNNs) are an evolving Machine Learning (ML) method that has proved its ability in various classification tasks. Convolutional Neural Networks (CNNs) present the optimal results for changing image classification tasks. In this regard, this study focused on developing a Multi-versus Optimizer with Deep Learning Enabled Robust Medical X-ray Image Classification (MVODL-RMXIC) method, aiming to identify abnormalities in medical X-ray images. The MVODL-RMXIC model used the Cross Bilateral Filtering (CBF) technique for noise removal, a MixNet feature extractor with an MVO algorithm based on hyperparameter optimization, and Bidirectional Long-Short-Term Memory (BiLSTM) for image classification. The proposed MVODL-RMXIC model was simulated and evaluated, showing its efficiency over other current methods. https://etasr.com/index.php/ETASR/article/view/6127medical x-ray imagesbiomedical imagingimage classificationdeep learningmulti-versus optimizer |
| spellingShingle | Thirugnanam Kumar Ramasamy Ponnusamy Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus Optimizer Engineering, Technology & Applied Science Research medical x-ray images biomedical imaging image classification deep learning multi-versus optimizer |
| title | Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus Optimizer |
| title_full | Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus Optimizer |
| title_fullStr | Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus Optimizer |
| title_full_unstemmed | Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus Optimizer |
| title_short | Robust Medical X-Ray Image Classification by Deep Learning with Multi-Versus Optimizer |
| title_sort | robust medical x ray image classification by deep learning with multi versus optimizer |
| topic | medical x-ray images biomedical imaging image classification deep learning multi-versus optimizer |
| url | https://etasr.com/index.php/ETASR/article/view/6127 |
| work_keys_str_mv | AT thirugnanamkumar robustmedicalxrayimageclassificationbydeeplearningwithmultiversusoptimizer AT ramasamyponnusamy robustmedicalxrayimageclassificationbydeeplearningwithmultiversusoptimizer |