Machine Learning and Infrared Thermography for Breast Cancer Detection
| Autor: | Lucimara E. Oliveira, Caroline B Gonçalves, Henrique Fernandes, Amanda C. Q. Leles, Gilmar Guimaraes, Juliano R. Cunha |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Early breast cancer detection
Artificial neural network Computer science business.industry Cancer lcsh:A medicine.disease Machine learning computer.software_genre Support vector machine Breast cancer breast cancer machine learning Thermography infrared thermography medicine Artificial intelligence lcsh:General Works business computer |
| Zdroj: | Proceedings, Vol 27, Iss 1, p 45 (2019) |
| ISSN: | 2504-3900 |
| Popis: | Breast cancer kills a large number of women around the world. Infrared thermography is a promising screening technique which does not involve harmful radiation for the patient and has a relatively low cost. This work proposes an approach for classifying patients into three different classes using infrared images: healthy patients, patients with benign changes and patients with cancer (malignant changes). A set of features is extracted from each image and two approaches are used in the classification process. The first is based on Artificial Neural Networks while the second is based on Support Vector Machines. The proposed approach shows a great potential to be used as a screening diagnosis technique for early breast cancer detection. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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