Breast Symmetry Classification: A Proposal of Image Analysis Based Indices
Abstract
The study aims to develop a method for evaluating breast symmetry using profile images. This shape-based analysis assesses differences between the two profiles with the help of simple indices, enabling an external symmetry evaluation independent of the image acquisition method. Initially, thermograms of 62 volunteers were analyzed, leading to the proposal of four asymmetry indices based on measurements of breast profile. Subsequently, images from 30 additional volunteers were examined to determine whether a multimodal pattern emerged across different imaging techniques, including infrared (IR) cameras, three-dimensional (3D) scan models, and photographic (RGB) cameras. To validate the method and assess the feasibility of applying the proposed indices to these imaging methods, the classified images (as symmetric or asymmetric) were evaluated by 28 specialists. The comparison between the proposed indices and expert assessments resulted in an accuracy rate of 60%.
Keywords:
thermography, breast cancer, breast asymmetry
References
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L.F. Silva, D. C. M. Saade, G. O. Sequeiros, A. C. Silva, A. C. Paiva, R. S. Bravo, and A. Conci. 2014. A new database for mastology research with infrared image. Journal of Medical Imaging and Health Informatics 4, 1 (2014), 92–100. DOI: 10.1166/jmihi.2014.1226
Brasil. 1999. Lei Nº 9.797, de 6 de maio de 1999. [link]. Dispõe sobre a cirurgia plástica reparadora da mama..
BRASIL. 2023. Procedimentos Hospitalares do SUS - Por Local de Internação. Brasília, DF: Ministério da Saúde. [link]
J. S. Cardoso and M. J. Cardoso. 2007. Towards an Intelligent Medical System for the Aesthetic Evaluation of Breast Cancer Conservative Treatment. Artif Intell Med (2007). DOI: 10.1016/j.artmed.2007.02.007 Epub 2007 Apr 8. PMID: 17420117.
M.J. Cardoso, J.S. Cardoso, H.P. Oliveira, and P. Gouveia. 2015. The Breast Cancer Conservative Treatment. Cosmetic Results - BCCT.core - Software for Objective Assessment of Esthetic Outcome in Breast Cancer Conservative Treatment: A Narrative Review. Universidade do Porto. In Comput Methods Programs Biomed (2015). DOI: 10.1016/j.cmpb.2015.11.010 Epub 2015 Dec 9. PMID: 26707372.
E. C. Carvalho, A. M. Coelho, A. Conci, and M. F. O. Baffa. 2023. U-Net Convolutional Neural Networks for breast IR imaging segmentation on frontal and lateral view. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 11, 3 (2023), 311–316. DOI: 10.1080/21681163.2022.2040053
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Mahnaz Etehadtavakol, Mojtaba Sirati-Amsheh, Golnaz Moallem, and Eddie Yin Kwee Ng. 2025. Enhancing thyroid nodule classification: A comprehensive analysis of feature selection in thermography. Infrared Physics Technology 145 (2025), 105730. DOI: 10.1016/j.infrared.2025.105730
G. Gallo, D. Allegra, Y. G. Atani, F. L. M. Milotta, F. Stanco, and G. Catanuto. 2016. Breast Shape Parametrization Through Planar Projections. In Lecture Notes in Computer Science. 135–146. DOI: 10.1007/978-3-319-48680-2_13
M. Gezimati and G. Singh. 2025. Deep Learning for Multimodal Breast Cancer Characterization with Emergence of Terahertz and Infrared Imaging. IEEE Transactions on Instrumentation and Measurement (2025), 1–1. DOI: 10.1109/TIM.2025. 3547084
ISAPS. 2023. International Survey on Aesthetic/Cosmetic Procedures Performed in 2023. [link]
D. Menezes, W. Fiorotti, L. Lima, E. Constantino, R. Leal, J. Landeiro, A. Conci, and M. Acioly. 2024. High-resolution intraoperative infrared thermography for the functional imaging and tumor resection maximization of a low-grade glioma: Technical case report. Journal of Clinical Images and Medical Case Reports 5 (2024), 5pp. DOI: 10.52768/2766-7820/2933, Open Access.
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D.P. Navarro. 2017. Desenvolvimento de um Sistema Computacional para Avaliação de Simetria Mamária. Master’s thesis. Universidade Positivo. [link]
G. Novita, E. Millen, F. Zerwes, F. Pimentel, H. Oliveira Filho, and J. Pena Reis. 2025. Tenho Doença de Paget da Mama, e agora? [link] Acessado em: 10 mar. 2025.
R. Pacholczak, W. Klimek-Piotrowska, and P. Kuszmiersz. 2016. Associations of anthropometric measures on breast cancer risk in pre- and post-menopausal women–a case-control study. Journal of Physiological Anthropology 35 (3 2016), 7. DOI: 10.1186/s40101-016-0090-x
N. Princigalli, A. E. L. S. Moura, and A. Conci. 2023. Could the Consideration of Symmetry be Statistically Significant for Breast Infrared Analysis?. In Artificial Intelligence over Infrared Images for Medical Applications. AIIIMA 2023 (Lecture Notes in Computer Science, Vol. 14298), S.T. Kakileti, G. Manjunath, R.G. Schwartz, and A.F. Frangi (Eds.). Springer, Cham, 67–79. DOI: 10.1007/978-3-031-44511-8_5
B. A. Sayed, A. S. Eldin, D. S. Elzanfaly, and A. S. Ghoneim. 2025. Breast Cancer Detection using Thermography and Convolutional Neural Networks (CNNs). In Proceedings of the 11th International Conference on Advanced Intelligent Systems and Informatics (AISI 2025), A. E. Hassanien, R. Y. Rizk, A. Darwish, M. T. R. Alshurideh, V. Snášel, and M. F. Tolba (Eds.). Lecture Notes on Data Engineering and Communications Technologies, Vol. 238. Springer, Cham. DOI: 10.1007/978-3-031-81308-5_16
L.F. Silva, D. C. M. Saade, G. O. Sequeiros, A. C. Silva, A. C. Paiva, R. S. Bravo, and A. Conci. 2014. A new database for mastology research with infrared image. Journal of Medical Imaging and Health Informatics 4, 1 (2014), 92–100. DOI: 10.1166/jmihi.2014.1226
Published
2025-06-03
How to Cite
MOURA, Eudóxia L. S.; PASTURA, Flávia C. H.; SCAGLIUSI, Natascha; OLIVEIRA, Wanessa I.; CONCI, Aura.
Breast Symmetry Classification: A Proposal of Image Analysis Based Indices. In: ACM INTERNATIONAL CONFERENCE ON INTERACTIVE MEDIA EXPERIENCES WORKSHOPS (IMXW), 25. , 2025, Niterói/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 64-69.
DOI: https://doi.org/10.5753/imxw.2025.5735.
