An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm
Early detection of melanoma is crucial in preventing death from this fatal skin cancer. Therefore, it would be valuable to develop a method that facilitates this process. The diagnosis of melanoma typically involves an invasive form of testing called a biopsy, as well as non-invasive intelligent app...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-10-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023083263 |
| _version_ | 1827780181663678464 |
|---|---|
| author | Qianqian Liu Hiroto Kawashima Asad Rezaei sofla |
| author_facet | Qianqian Liu Hiroto Kawashima Asad Rezaei sofla |
| author_sort | Qianqian Liu |
| collection | DOAJ |
| description | Early detection of melanoma is crucial in preventing death from this fatal skin cancer. Therefore, it would be valuable to develop a method that facilitates this process. The diagnosis of melanoma typically involves an invasive form of testing called a biopsy, as well as non-invasive intelligent approaches to diagnosis. In the present study a recent research, a novel approach has been developed for the optimal detection of melanoma cancer. The method uses reinforcement learning for segmenting the skin regions, followed by the extraction and selection of useful features using the Enhanced Fish Migration Optimizer (EFMO) algorithm. The outcomes get categorized on the basis of an optimized SVM on the basis of the EFMO algorithm. The recommended approach has been certified by applying it to the SIIM-ISIC dataset of Melanoma and comparing it with 12 other approaches. Simulations illustrated that the proposed method delivered the finest values compared to the others. |
| first_indexed | 2024-03-11T15:02:00Z |
| format | Article |
| id | doaj.art-a62c750bda2f432ea9bda3837f8b6061 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-11T15:02:00Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-a62c750bda2f432ea9bda3837f8b60612023-10-30T06:08:21ZengElsevierHeliyon2405-84402023-10-01910e21118An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithmQianqian Liu0Hiroto Kawashima1Asad Rezaei sofla2Laboratory of Microbiology and Immunology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 260-8675, JapanLaboratory of Microbiology and Immunology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 260-8675, Japan; Corresponding authorUniversity of Tehran, Tehran, Iran; College of Technical Engineering, The Islamic University, Najaf, IraqEarly detection of melanoma is crucial in preventing death from this fatal skin cancer. Therefore, it would be valuable to develop a method that facilitates this process. The diagnosis of melanoma typically involves an invasive form of testing called a biopsy, as well as non-invasive intelligent approaches to diagnosis. In the present study a recent research, a novel approach has been developed for the optimal detection of melanoma cancer. The method uses reinforcement learning for segmenting the skin regions, followed by the extraction and selection of useful features using the Enhanced Fish Migration Optimizer (EFMO) algorithm. The outcomes get categorized on the basis of an optimized SVM on the basis of the EFMO algorithm. The recommended approach has been certified by applying it to the SIIM-ISIC dataset of Melanoma and comparing it with 12 other approaches. Simulations illustrated that the proposed method delivered the finest values compared to the others.http://www.sciencedirect.com/science/article/pii/S2405844023083263Melanoma detectionFeature selectionReinforcement learningEnhanced fish migration optimizer (EFMO)Feature extractionSupport vector machine |
| spellingShingle | Qianqian Liu Hiroto Kawashima Asad Rezaei sofla An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm Heliyon Melanoma detection Feature selection Reinforcement learning Enhanced fish migration optimizer (EFMO) Feature extraction Support vector machine |
| title | An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm |
| title_full | An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm |
| title_fullStr | An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm |
| title_full_unstemmed | An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm |
| title_short | An optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm |
| title_sort | optimal method for melanoma detection from dermoscopy images using reinforcement learning and support vector machine optimized by enhanced fish migration optimization algorithm |
| topic | Melanoma detection Feature selection Reinforcement learning Enhanced fish migration optimizer (EFMO) Feature extraction Support vector machine |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023083263 |
| work_keys_str_mv | AT qianqianliu anoptimalmethodformelanomadetectionfromdermoscopyimagesusingreinforcementlearningandsupportvectormachineoptimizedbyenhancedfishmigrationoptimizationalgorithm AT hirotokawashima anoptimalmethodformelanomadetectionfromdermoscopyimagesusingreinforcementlearningandsupportvectormachineoptimizedbyenhancedfishmigrationoptimizationalgorithm AT asadrezaeisofla anoptimalmethodformelanomadetectionfromdermoscopyimagesusingreinforcementlearningandsupportvectormachineoptimizedbyenhancedfishmigrationoptimizationalgorithm AT qianqianliu optimalmethodformelanomadetectionfromdermoscopyimagesusingreinforcementlearningandsupportvectormachineoptimizedbyenhancedfishmigrationoptimizationalgorithm AT hirotokawashima optimalmethodformelanomadetectionfromdermoscopyimagesusingreinforcementlearningandsupportvectormachineoptimizedbyenhancedfishmigrationoptimizationalgorithm AT asadrezaeisofla optimalmethodformelanomadetectionfromdermoscopyimagesusingreinforcementlearningandsupportvectormachineoptimizedbyenhancedfishmigrationoptimizationalgorithm |