STUDY AND ANALYSIS OF IMAGE QUALITY METRICS IN DIGITAL MAMMOGRAPHIC SYSTEMS IN CLINICAL CONDITIONS

• Grant number: 24/20390-2
• Support Opportunities: Scholarships in Brazil - Master
• Start date: August 01, 2025
• End date: April 30, 2026
• Field of knowledge: Health Sciences - Medicine - Medical Radiology
• Principal Investigator: Martin Eduardo Poletti
• Grantee: Laura Alcântara Silva Lopes
• Host Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

One of the leading causes of global mortality is related to tissue neoplasms. Specifically, breast cancer remains the second most frequent type of cancer in Brazil and the most common among women. Early detection significantly reduces the risk of mortality in individuals affected by this disease. Currently, mammography is the most effective technique for early detection of breast cancer. However, the mammographic image quality is influenced by several factors, such as magnification, acquisition geometry, scattered radiation, the use of antiscatter grids, and the detection system. Although various metrics exist to evaluate the performance of mammographic systems, most focus solely on the detection system by determinating the quantum detection efficiency, overlooking other factors that define clinically relevant conditions and may compromise diagnosis effectiveness. This project's main objective is the detailed study and analysis of several digital mammographic systems using quantitative metrics that consider critical factors related to image quality under clinically relevant conditions, which are often not comprehensively addressed in the literature. The results obtained will help identify conditions that can increase the sensitivity of digital mammography and reduce the risks associated with breast exposure to ionizing radiation, as well as allow for performance comparisons between different digital mammography systems currently in use. Thus, the information obtained in this study is crucial for the health area, as it is associated with the development and optimization of breast imaging techniques, allowing for improvements in the early detection of breast cancer and positively impacting the reduction of mortality rates. (AU)