Univ Angers, LARIS - Laboratoire Angevin de Recherche en Ingénierie des Systèmes, 62 avenue Notre-Dame du Lac, 49000, Angers, France.
Department of Physiology, School of Medicine of Ribeirao Preto, University of Sao Paulo, Ribeirao Preto, SP, Brazil.
Comput Biol Med. 2018 Sep 1;100:36-40. doi: 10.1016/j.compbiomed.2018.06.021. Epub 2018 Jun 25.
The multiscale entropy (MSE) measure is now widely used to quantify the complexity of time series. The development of complexity measures for images is also a long-standing goal. Recently, the bi-dimensional version of MSE has been proposed (MSE) to analyze images. The interpretation of MSE curves and the applications to real data are still emergent. Because the coarse-graining step in the MSE computation changes the frequency content of the image, we hypothesized a possible dependence between MSE and the discrete Fourier transform (DFT). To analyze this dependence, synthetic as well as biomedical images are analyzed. Our results reveal that i) the profile of MSE is sensitive to both the amplitude and phase of the DFT; ii) MSE could find applications in the biomedical field. This work brings valuable information for MSE interpretation and opens possibilities to study images from an entropy point of view through spatial scales.
多尺度熵（MSE）测度现在被广泛用于量化时间序列的复杂性。分析图像的复杂性测度也是一个长期以来的目标。最近，提出了二维版本的 MSE（MSE）来分析图像。MSE 曲线的解释和对实际数据的应用仍然是新兴的。由于 MSE 计算中的粗粒化步骤改变了图像的频率内容，我们假设 MSE 与离散傅里叶变换（DFT）之间可能存在依赖关系。为了分析这种依赖性，我们分析了合成图像和生物医学图像。我们的结果表明：i）MSE 的轮廓对 DFT 的幅度和相位都很敏感；ii）MSE 可以在生物医学领域找到应用。这项工作为 MSE 的解释提供了有价值的信息，并为通过空间尺度从熵的角度研究图像开辟了可能性。
