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Automatic Quantification of Breast Arterial Calcification on Mammographic Images

Title: Automatic Quantification of Breast Arterial Calcification on Mammographic Images
Authors: Mazidi, N; Roobottom, C; Masala, G
Publisher Information: Springer Nature
Publication Year: 2019
Collection: eSpace - Manchester Metropolitan University's Research Repository
Description: © 2019, Springer Nature Singapore Pte Ltd. This paper describes the research and development of an automatic computer system that is used to quantify breast arterial calcifications in mammography scans. A few prior studies have attempted to establish a relationship between breast arterial calcification (BAC) and the rate of coronary artery disease (CAD) risk factors. The majority of these studies demonstrated a positive association between BAC and increasing age. Large scale cohort studies and retrospective studies have almost uniformly suggested a strong association between BAC and cardiovascular disease-related morbidity and mortality. This strong association of BAC with cardiovascular pathology suggests that BAC should also be persistently associated with radiographically determined CAD. A method of image processing, segmentation, and quantification used to highlight and recognise calcified blood vessels in the breast is proposed and described in detail. This project aims to introduce a new use for digital Mammography, which is currently solely used for diagnosing breast cancer in female patients. A method of detecting BAC is introduced at no additional cost, having an adequate degree of accuracy, around 82%, which means that this type of system could be used to assist a radiographer in diagnosing BAC by indicating whether the patient has a high or low severity of calcification.
Document Type: conference object
File Description: text
Language: English
Relation: https://e-space.mmu.ac.uk/623234/; https://link.springer.com/chapter/10.1007%2F978-981-13-8566-7_28
Availability: https://e-space.mmu.ac.uk/623234/1/imed19-001.pdf
Rights: in_copyright ; info:eu-repo/semantics/openAccess
Accession Number: edsbas.1FAE078B
Database: BASE