| Autor: |
Anupama Y K, Amutha S, null Ramesh Babu D R, null S. Sathish Kumar |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
International Journal of Online and Biomedical Engineering (iJOE). 19:81-96 |
| ISSN: |
2626-8493 |
| DOI: |
10.3991/ijoe.v19i06.37891 |
| Popis: |
Breast cancer is one of the most affecting carcinoma for women from long time. Early detection is necessary to increase the lifespan of patients. In this study deep learning and machine learning approaches are applied to histopathological, mammogram and ultrasound breast cancer modalities. In- order to increase the efficacy of diagnosis of these modalities. Study has been carried out in majorly four phases. First phase involved collection of the datasets of all the three modalities mentioned earlier. Second phase consists of extracting relevant features using Resnet-18. Third phase involves feeding the extracted information to enhanced firefly or to the existing optimization techniques. Fourth phase consists of considering selected features as input to the classifiers. Then enhanced firefly based classifier compared with the existing ant colony and genetic algorithm based classifier. Enhanced firefly based classifier displays better results compared to the state of art approaches. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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