ArticleIEEE transactions on medical imaging2012
Shape-based regularization of electron tomographic reconstruction.
Article in IEEE transactions on medical imaging, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- SHAPE BASED IMAGE RECONSTRUCTION USING LINEARIZED DEFORMATIONS.Inverse problems · 2017Article
- A Survey of the Use of Iterative Reconstruction Algorithms in Electron Microscopy.BioMed research international · 2017Review
- Compressed Sensing Electron Tomography for Determining Biological Structure.Scientific reports · 2016Article
- Compensation of missing wedge effects with sequential statistical reconstruction in electron tomography.PloS one · 2014Article
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6 authors.
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Abstract
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.
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