Repositori institucional URV
| URV's Author/s: | Abdelnasser Mohamed Mahmoud, Mohamed / Moreno Ribas, Antonio / Puig Valls, Domènec Savi |
| Author, as appears in the article.: | Abdel-Nasser, Mohamed; Moreno, Antonio; Puig, Domenec |
| Author's mail: | mohamed.abdelnasser@urv.cat antonio.moreno@urv.cat domenec.puig@urv.cat |
| Author identifier: | 0000-0002-1074-2441 0000-0003-3945-2314 0000-0002-0562-4205 |
| Journal publication year: | 2019 |
| Publication Type: | Journal Publications |
| ISSN: | 08834989 |
| e-ISSN: | 0883-4989 |
| APA: | Abdel-Nasser, Mohamed; Moreno, Antonio; Puig, Domenec (2019). Breast cancer detection in thermal infrared images using representation learning and texture analysis methods. Electronics, 8(1), 100-. DOI: 10.3390/electronics8010100 |
| Paper original source: | Electronics. 8 (1): 100- |
| Abstract: | © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Nowadays, breast cancer is one of the most common cancers diagnosed in women. Mammography is the standard screening imaging technique for the early detection of breast cancer. However, thermal infrared images (thermographies) can be used to reveal lesions in dense breasts. In these images, the temperature of the regions that contain tumors is warmer than the normal tissue. To detect that difference in temperature between normal and cancerous regions, a dynamic thermography procedure uses thermal infrared cameras to generate infrared images at fixed time steps, obtaining a sequence of infrared images. In this paper, we propose a novel method to model the changes on temperatures in normal and abnormal breasts using a representation learning technique called learning-to-rank and texture analysis methods. The proposed method generates a compact representation for the infrared images of each sequence, which is then exploited to differentiate between normal and cancerous cases. Our method produced competitive (AUC = 0.989) results when compared to other studies in the literature. |
| Article's DOI: | 10.3390/electronics8010100 |
| Link to the original source: | https://www.mdpi.com/2079-9292/8/1/100 |
| Paper version: | info:eu-repo/semantics/publishedVersion |
| licence for use: | https://creativecommons.org/licenses/by/3.0/es/ |
| Department: | Enginyeria Informàtica i Matemàtiques |
| Licence document URL: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
| Thematic Areas: | Signal processing Physics, applied Hardware and architecture Engineering, electrical & electronic Engenharias iv Electrical and electronic engineering Control and systems engineering Computer science, information systems Computer networks and communications |
| Keywords: | Thermography Thermal infrared images Texture analysis Statistics Representation learning Mammography Machine learning Features Database Computer-aided diagnosis systems Classification Breast cancer |
| Entity: | Universitat Rovira i Virgili |
| Record's date: | 2024-10-12 |
| Journal volume: | 8 |
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