A Review on Automatic Mammographic Density and Parenchymal Segmentation
Joint Authors
He, Wenda
Juette, Arne
Denton, Erika R. E.
Oliver, Arnau
Martí, Robert
Zwiggelaar, Reyer
Source
International Journal of Breast Cancer
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-31, 31 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-11
Country of Publication
Egypt
No. of Pages
31
Main Subjects
Abstract EN
Breast cancer is the most frequently diagnosed cancer in women.
However, the exact cause(s) of breast cancer still remains unknown.
Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer.
There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models).
Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches.
Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment.
This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation.
The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models.
American Psychological Association (APA)
He, Wenda& Juette, Arne& Denton, Erika R. E.& Oliver, Arnau& Martí, Robert& Zwiggelaar, Reyer. 2015. A Review on Automatic Mammographic Density and Parenchymal Segmentation. International Journal of Breast Cancer،Vol. 2015, no. 2015, pp.1-31.
https://search.emarefa.net/detail/BIM-1065260
Modern Language Association (MLA)
He, Wenda…[et al.]. A Review on Automatic Mammographic Density and Parenchymal Segmentation. International Journal of Breast Cancer No. 2015 (2015), pp.1-31.
https://search.emarefa.net/detail/BIM-1065260
American Medical Association (AMA)
He, Wenda& Juette, Arne& Denton, Erika R. E.& Oliver, Arnau& Martí, Robert& Zwiggelaar, Reyer. A Review on Automatic Mammographic Density and Parenchymal Segmentation. International Journal of Breast Cancer. 2015. Vol. 2015, no. 2015, pp.1-31.
https://search.emarefa.net/detail/BIM-1065260
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1065260