Articles producció científica> Enginyeria Informàtica i Matemàtiques

Breast cancer detection in thermal infrared images using representation learning and texture analysis methods

  • Dades identificatives

    Identificador: imarina:4225097
    Handle: https://hdl.handle.net/20.500.11797/imarina4225097
    Autors:
    Abdel-Nasser, MohamedMoreno, AntonioPuig, Domenec
    Resum:
    © 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.

  • Altres:

    Autor segons l'article: Abdel-Nasser, Mohamed; Moreno, Antonio; Puig, Domenec
    Departament: Enginyeria Informàtica i Matemàtiques
    e-ISSN: 0883-4989
    Autor/s de la URV: Abdelnasser Mohamed Mahmoud, Mohamed / Moreno Ribas, Antonio / Puig Valls, Domènec Savi
    Paraules clau: Thermography Thermal infrared images Texture analysis Statistics Representation learning Mammography Machine learning Features Database Computer-aided diagnosis systems Classification Breast cancer
    Resum: © 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.
    Àrees temàtiques: 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
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 08834989
    Adreça de correu electrònic de l'autor: mohamed.abdelnasser@urv.cat antonio.moreno@urv.cat domenec.puig@urv.cat
    Identificador de l'autor: 0000-0002-1074-2441 0000-0003-3945-2314 0000-0002-0562-4205
    Data d'alta del registre: 2024-10-12
    Volum de revista: 8
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Electronics. 8 (1): 100-
    Referència de l'ítem segons les normes 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
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2019
    Tipus de publicació: Journal Publications

  • Paraules clau:

    Computer Networks and Communications,Computer Science, Information Systems,Control and Systems Engineering,Electrical and Electronic Engineering,Engineering, Electrical & Electronic,Hardware and Architecture,Physics, Applied,Signal Processing
    Thermography
    Thermal infrared images
    Texture analysis
    Statistics
    Representation learning
    Mammography
    Machine learning
    Features
    Database
    Computer-aided diagnosis systems
    Classification
    Breast cancer
    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

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