Time Series Analysis of Breast Thermal Signals for Anomaly Detection

• Lincoln F. Silva UFF
• Giomar O. S. Olivera UFF
• Stephenson Galvão UFF
• Jéssica B. Silva UFF
• Alair Augusto S. M. D. Santos UFF
• Débora C. Muchaluat-Saade UFF
• Aura Conci UFF

Abstract

Breast cancer is the second most common cancer in the world. Currently, there are no effective methods to prevent this disease. However, diagnosis in early stages increases cure chances. Breast thermography is an additional option to be considered in screening strategies. In this article, an analysis is carried out about the thermal signals of patients with and without healthy breasts. These signals are produced from twenty thermograms captured by dynamic infrared thermography. Initially the images of each patient are registered. Then, the region of the breast is divided into regions with size 3x3 pixels and the average temperature, from each of these regions, is observed in the twenty images of the sequence. Features of the time series of such 3x3 regions are calculated. These features present different behaviour between healthy and unhealthy breasts. Among the differences, the main has been found in the signal complexity feature, the standard deviation of the values calculated was 0.234, for healthy patients, and 0.052, for sick patients.

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