Shape-based regularization of electron tomographic reconstruction.
Shape-based regularization of electron tomographic reconstruction.
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DOI：
10.1109/tmi.2012.2214229
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发表时间：
2012-12
影响因子：
10.6
通讯作者：
Bajaj C
中科院分区：
文献类型：
--
作者：
Gopinath A;Xu G;Ress D;Öktem O;Subramaniam S;Bajaj C
本文介绍了一种利用基于形状的正则化技术实现的层析重建方法。将重构结构中已知特征的空间模型作为正则化器集成到重构过程中。我们的正则化方案通过分割得到的形状信息进行局部驱动，并与已知的空间模型进行比较。我们在病毒复合体的数字幻影、模拟数据和实验电子断层扫描（ET）数据上展示了我们的方法。我们的重建显示减少了模糊，重建体积的分辨率也得到了提高。与加权反向投影和代数重建技术等流行技术相比，该方法还改进了病毒膜上刺突边界的划分。改进的ET重建将提供更好的结构阐明和改进的特征可视化，这有助于解决关键的生物学问题。我们的方法也可以推广到其他层析模式。
We introduce a tomographic reconstruction method implemented using a shape based regularization technique. Spatial models of known features in the structure being reconstructed are integrated into the reconstruction process as regularizers. Our regularization scheme is driven locally through shape information obtained from segmentation and compared with a known spatial model. We demonstrated our method on tomography data from digital phantoms, simulated data and experimental Electron Tomography (ET) data of virus complexes. Our reconstruction showed reduced blurring and an improvement in the resolution of the reconstructed volume was also measured. This method also produced improved demarcation of spike boundaries in viral membranes when compared with popular techniques like Weighted Back Projection and the Algebraic Reconstruction Technique. Improved ET reconstructions will provide better structure elucidation and improved feature visualization, which can aid in solving key biological issues. Our method can also be generalized to other tomographic modalities.