Automatic Computation of the Posterior Nipple Line from Mammographies

Quynh Tran, Tina Santner, Antonio Rodríguez-Sánchez

2024

Abstract

Breast cancer is the most commonly diagnosed cancer in female patients. Detecting early signs of malignity by undergoing breast screening is therefore of great importance. For a reliable diagnosis, high-quality exami-nated mammograms are essential since poor breast positioning can cause cancers to be missed, which is why mammograms are subject to strict evaluation criteria. One such criterion is the posterior (or pectoralis) nipple line (PNL). We present a method for computing the PNL length, which consisted of the following steps: Pectoral Muscle Detection, Nipple Detection, and final PNL Computation. A multidirectional Gabor filter allowed us to detect the pectoral muscle. For detecting the nipple we made use of the geometric properties of the breast, applied watershed segmentation and Hough Circle Transform. Using both landmarks (pectoral muscle and nipple), the PNL length could be computed. We evaluated 100 mammogram images provided by the Medical University of Innsbruck. The computed PNL length was compared with the real PNL length, which was measured by an expert. Our methodology achieved an absolute mean error of just 6.39 mm.

Paper Citation

in Harvard Style

Tran Q., Santner T. and Rodríguez-Sánchez A. (2024). Automatic Computation of the Posterior Nipple Line from Mammographies. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 629-636. DOI: 10.5220/0012570500003660

in Bibtex Style

@conference{visapp24,
author={Quynh Tran and Tina Santner and Antonio Rodríguez-Sánchez},
title={Automatic Computation of the Posterior Nipple Line from Mammographies},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={629-636},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012570500003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - Automatic Computation of the Posterior Nipple Line from Mammographies
SN - 978-989-758-679-8
AU - Tran Q.
AU - Santner T.
AU - Rodríguez-Sánchez A.
PY - 2024
SP - 629
EP - 636
DO - 10.5220/0012570500003660
PB - SciTePress