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TITLE:
Breast Tumor Classification in Digital Tomosynthesis Based on Deep Learning Radiomics - imarina:9385564

URV's Author/s:Abdelnasser Mohamed Mahmoud, Mohamed / Puig Valls, Domènec Savi
Author, as appears in the article.:Hassan, Loay; Abdel-Nasser, Mohamed; Saleh, Adel; Puig, Domenec
Author's mail:domenec.puig@urv.cat
mohamed.abdelnasser@urv.cat
Author identifier:0000-0002-0562-4205
0000-0002-1074-2441
Journal publication year:2022
Publication Type:Proceedings Paper
APA:Hassan, Loay; Abdel-Nasser, Mohamed; Saleh, Adel; Puig, Domenec (2022). Breast Tumor Classification in Digital Tomosynthesis Based on Deep Learning Radiomics. Amsterdam: IOS Press
Papper original source:Frontiers In Artificial Intelligence And Applications. 356 269-278
Abstract:Breast cancer is the most frequently diagnosed cancer in women globally. Early and accurate detection and classification of breast tumors are critical in improving treatment strategies and increasing the patient survival rate. Digital breast tomosynthesis (DBT) is an advanced form of mammography that aids better in the early detection and diagnosis of breast disease. This paper proposes a breast tumor classification method based on analyzing and evaluating the performance of various of the most innovative deep learning classification models in cooperation with a support vector machine (SVM) classifier for a DBT dataset. Specifically, we study the ability to use transfer learning from non-medical images to classify tumors in unseen DBT medical images. In addition, we utilize the fine-tuning technique to improve classification accuracy.
Article's DOI:10.3233/FAIA220348
Link to the original source:https://ebooks.iospress.nl/doi/10.3233/FAIA220348
Papper 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:Artificial intelligence
Ciências agrárias i
Comunicació i informació
Engenharias iii
Engenharias iv
General o multidisciplinar
Información y documentación
Interdisciplinar
Medicina ii
Keywords:Breast cancer classification
Brest cancer classification
Computer vision
Deep learning
Digital breast tomosynthesis
Support vector machin
Support vector machine
Entity:Universitat Rovira i Virgili
Record's date:2024-10-12
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