Author, as appears in the article.: Abdel-Nasser, Mohamed; Saleh, Adel; Moreno, Antonio; Puig, Domenec
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Abdelnasser Mohamed Mahmoud, Mohamed / Moreno Ribas, Antonio / Puig Valls, Domènec Savi
Keywords: Thermography (temperature measurement) Thermograms Temperature measuring instruments Nipple detection Medical imaging Infrared radiation Infrared imaging Infrared Image segmentation Feature extraction Early detection of breast cancer Diseases Diagnosis Computer aided diagnosis(cad) Computer aided diagnosis Breast cancer classifications Breast cancer cad systems Breast cancer Adaptive thresholding
Abstract: Breast cancer is one of the most dangerous diseases for women. Detecting breast cancer in its early stage may lead to a reduction in mortality. Although the study of mammographies is the most common method to detect breast cancer, it is outperformed by the analysis of thermographies in dense tissue (breasts of young women). In the last two decades, several computer-aided diagnosis (CAD) systems for the early detection of breast cancer have been proposed. Breast cancer CAD systems consist of many steps, such as segmentation of the region of interest, feature extraction, classification and nipple detection. Indeed, the nipple is an important anatomical landmark in thermograms. The location of the nipple is invaluable in the analysis of medical images because it can be used in several applications, such as image registration and modality fusion. This paper proposes an unsupervised, automatic, accurate, simple and fast method to detect nipples in thermograms. The main stages of the proposed method are: human body segmentation, determination of nipple candidates using adaptive thresholding and detection of the nipples using a novel selection algorithm. Experiments have been carried out on a thermograms dataset to validate the proposed method, achieving accurate nipple detection results in real-time. We also show an application of the proposed method, breast cancer classification in dynamic images, where the new nipple detection technique is used to segment the region of the two breasts from the infrared image. A dataset of dynamic thermograms has been used to validate this application, achieving good results. © 2016 Elsevier Ltd
Thematic Areas: Química Operations research & management science Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General engineering Farmacia Engineering, electrical & electronic Engineering (miscellaneous) Engineering (all) Engenharias iv Engenharias iii Engenharias ii Engenharias i Enfermagem Educação Economia Direito Computer science, artificial intelligence Computer science applications Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología Biodiversidade Astronomia / física Artificial intelligence Arquitetura, urbanismo e design Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
licence for use: https://creativecommons.org/licenses/by/3.0/es/
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
Record's date: 2024-10-12
Papper version: info:eu-repo/semantics/acceptedVersion
Link to the original source: https://www.sciencedirect.com/science/article/abs/pii/S095741741630416X?via%3Dihub
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Expert Systems With Applications. 64 365-374
APA: Abdel-Nasser, Mohamed; Saleh, Adel; Moreno, Antonio; Puig, Domenec (2016). Automatic nipple detection in breast thermograms. Expert Systems With Applications, 64(), 365-374. DOI: 10.1016/j.eswa.2016.08.026
Article's DOI: 10.1016/j.eswa.2016.08.026
Entity: Universitat Rovira i Virgili
Journal publication year: 2016
Publication Type: Journal Publications