Santos W P, Assis F M, Souza R E, Santos Filho P B, Lima Neto F B
Universidade de Pernambuco, Escola Politécnica de Pernambuco, Madalena, Recife, PE, 50720-001, Brazil.
Comput Med Imaging Graph. 2009 Sep;33(6):442-60. doi: 10.1016/j.compmedimag.2009.04.004. Epub 2009 May 14.
Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. A considerable number of current methods of analysis are based on parametric statistics. Alternatively, some methods in computational intelligence are inspired by biology and other sciences. Here we claim that philosophy can be also considered as a source of inspiration. This work proposes the objective dialectical method (ODM): a method for classification based on the philosophy of praxis. ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, multispectral images are composed of diffusion-weighted (DW) magnetic resonance (MR) images. The results are compared to ground-truth images produced by polynomial networks using a morphological similarity index. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map. Such results proved that gray and white matter can be distinguished in DW-MR multispectral analysis and, consequently, DW-MR images can also be used to furnish anatomical information.
多光谱图像分析是一个相对有前景的研究领域，在医学成像和卫星监测等多个领域都有应用。当前相当多的分析方法基于参数统计。另外，计算智能中的一些方法受到生物学和其他科学的启发。在此我们声称哲学也可被视为灵感来源。这项工作提出了客观辩证方法（ODM）：一种基于实践哲学的分类方法。ODM有助于组装可演化的数学工具来分析多光谱图像。在本文所述的案例研究中，多光谱图像由扩散加权（DW）磁共振（MR）图像组成。使用形态相似性指数将结果与多项式网络生成的真实图像进行比较。分类结果用于改进表观扩散系数图的常规分析。这些结果证明，在DW-MR多光谱分析中可以区分灰质和白质，因此，DW-MR图像也可用于提供解剖学信息。
