Garduño Edgar, Wong-Barnum Mona, Volkmann Niels, Ellisman Mark H
Depto. Ciencias de la Computación, Instituto de Investigaciones en Matermáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Circuito Escolar S/N, Cd. Universitaria, C.P. 04510, Mexico City, Mexico.
J Struct Biol. 2008 Jun;162(3):368-79. doi: 10.1016/j.jsb.2008.01.017. Epub 2008 Feb 16.
In electron tomography the reconstructed density function is typically corrupted by noise and artifacts. Under those conditions, separating the meaningful regions of the reconstructed density function is not trivial. Despite development efforts that specifically target electron tomography manual segmentation continues to be the preferred method. Based on previous good experiences using a segmentation based on fuzzy logic principles (fuzzy segmentation) where the reconstructed density functions also have low signal-to-noise ratio, we applied it to electron tomographic reconstructions. We demonstrate the usefulness of the fuzzy segmentation algorithm evaluating it within the limits of segmenting electron tomograms of selectively stained, plastic embedded spiny dendrites. The results produced by the fuzzy segmentation algorithm within the framework presented are encouraging.
在电子断层扫描中，重建的密度函数通常会受到噪声和伪影的影响。在这些情况下，分离重建密度函数中有意义的区域并非易事。尽管有专门针对电子断层扫描的开发工作，但手动分割仍然是首选方法。基于先前在重建密度函数信噪比也较低的情况下使用基于模糊逻辑原理的分割方法（模糊分割）的良好经验，我们将其应用于电子断层扫描重建。我们通过在对选择性染色、塑料包埋的棘状树突进行电子断层扫描分割的范围内评估模糊分割算法，证明了该算法的有效性。在本文提出的框架内，模糊分割算法产生的结果令人鼓舞。
