Shape-based regularization of electron tomographic reconstruction
2012 (English)In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 31, no 12, 2241-2252 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
2012. Vol. 31, no 12, 2241-2252 p.
Bayesian methods, electron microscopy, reconstruction, shape-based regularization, tomography
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-111819DOI: 10.1109/TMI.2012.2214229ISI: 000313690600007ScopusID: 2-s2.0-84870490769OAI: oai:DiVA.org:kth-111819DiVA: diva2:587791
QC 201301152013-01-152013-01-142013-02-14Bibliographically approved