abstract

• Breast cancer, as a disease with high incidence among women, has motived computer science researchers to create support tools with the aim of helping radiologists its early detection, this is an important factor in the positive outcome of its treatment, which must be based according to the person, the type of cancer and its spread. Current research has based their work on computational methodologies without considering the medical methodologies followed by radiologists, mainly showing results as a binary classification of benign or malign. We present our preliminary results focusing on an activities diagram. This diagram shows a computational model based on a medical methodology, focusing on calcification recognition with the purpose of obtaining a BI-RADS classification. Our aim is to look for other ways to tackle this problem, so that computational systems could serve as an aid to radiologists, capable of showing results similar to those used by them. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

authors

• Castillo Barrera Francisco Edgar
• Martínez Pérez Francisco Eduardo
• Nava Muñoz Sandra Edith
• Nuñez-Varela A.S.
• Núñez Varela José Ignacio

publication date

• 2024-01-01

keywords

• Breast cancer; calcifications; computational conceptual model Lung cancer; 'current; Activity diagram; Binary classification; Breast Cancer; Calcification; Computational conceptual model; Computational methodology; Conceptual model; High incidence; Support tool; Calcification (biochemistry)

Digital Object Identifier (DOI)

• 10.1007/978-3-031-77571-0_44

PubMed ID

start page

• 467

end page

• 478

volume

• 1212 LNNS

issue