Abstract
Improved accurate measurement models and improved iterative reconstruction algorithms would benefit cryo-electron tomography (cryo-ET) performance. Filtered back- projection and related algorithms, successful in CT and MRI, assume a measurement model which is not well matched to the limited range of projection angles, large angular increments, and incomplete projections in cryo-ET. Iterative methods, such as compressed sensing (CS) can include irregular measurement models and spatial extent constraints, and have great potential for solution of severely under-determined systems. This paper uses source models with square and pyramidal basis functions and variable finite width aperture measurement to compare space domain and frequency domain CS reconstruction approaches in the cryo-ET context.
Original language | English (US) |
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Title of host publication | Conference Record - Asilomar Conference on Signals, Systems and Computers |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 760-764 |
Number of pages | 5 |
Volume | 2016-February |
ISBN (Print) | 9781467385763 |
DOIs | |
State | Published - Feb 26 2016 |
Event | 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States Duration: Nov 8 2015 → Nov 11 2015 |
Other
Other | 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 |
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Country | United States |
City | Pacific Grove |
Period | 11/8/15 → 11/11/15 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing