TOMOBFLOW: feature-preserving noise filtering for electron tomography. The program TOMOBFLOW (pronounced as tomo-be-flow) is intended for noise filtering with preservation of biologically relevant information. It is an efficient implementation of the Beltrami flow, a nonlinear filtering method that locally tunes the strength of the smoothing according to an edge indicator based on geometry properties. TOMOBFLOW is equipped with the power of diffusion-based filtering methods, with the important advantage that it does not require complicated parameter tuning for successful denoising of datasets. Furthermore, the program has been optimized to reduce the computational demands, specially in terms of memory requirements. In addition, code optimization and multithread programming has been used to exploit modern multicore computers. TOMOBFLOW reads and writes 3D datasets in MRC format. It is compatible with standard packages, which easily allows integration in the electron tomography workflow. A detailed description of the procedure implemented in the package can be found in the following article: TOMOBFLOW: Feature-preserving noise filtering for electron tomography. J.J. Fernandez. BMC Bioinformatics 2009, 10:178.

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References in zbMATH (referenced in 2 articles )

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  1. Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei: Multiscale geometric modeling of macromolecules. I: Cartesian representation (2014)
  2. Fernandez, Jose-Jesus: TOMOBFLOW: feature-preserving noise filtering for electron tomography (2009) ioport