anhaoz / sampensignatures

Sample Entropy Signatures for image feature extraction.

Sample Entropy Signatures

We present the Sample Entropy Signatures method, which provides a new way to represent images via Sample entropy (SampEn). The proposed method defines texture signatures from multiple SampEn values obtained from combinations of the parameters m and r. Here, m signatures were determined (m ranging from 1 to 4), with r points each (r ranging from 0.06 to 0.4), and the behavior of each signature was determined by the metrics: area under the curve, skewness, maximum entropy value, and area ratio. This approach aimed to improve the quantitative capacity of SampEn and provide a new interpretation of its values.

This code is also available on Code Ocean platform.

References

If you use this method on your research, please cite:

1. Rozendo, G. B., do Nascimento, M. Z., Roberto, G. F., de Faria, P. R., Silva, A. B., Tosta, T. A. A., & Neves, L. A. (2022). Classification of non-Hodgkin lymphomas based on sample entropy signatures. Expert Systems with Applications, 117238.

2. Rozendo, G. B., do Nascimento, M. Z., Roberto, G. F., de Faria, P. R., Silva, A. B., Tosta, T. A. A., & Neves, L. A. (2022). Sample Entropy Signatures: A new way to interpret SampEn values. Software Impacts, 100329.

3. Guilherme Botazzo Rozendo, Marcelo Zanchetta do Nascimento, Guilherme Freire Roberto, Paulo Rogério de Faria, Adriano Barbosa Silva, Thaína Aparecida Azevedo Tosta, Leandro Alves Neves (2022) Classification of Non-Hodgkin Lymphomas Based on Sample Entropy Signatures [Source Code]. https://doi.org/10.24433/CO.3053768.v1