Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/36730
Title: GPU-accelerated iterative reconstruction for limited-data tomography in CBCT systems.
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Issue Date: 2018
Citation: BMC Bioinformatics.2018 05;(19)1:171
Abstract: Standard cone-beam computed tomography (CBCT) involves the acquisition of at least 360 projections rotating through 360 degrees. Nevertheless, there are cases in which only a few projections can be taken in a limited angular span, such as during surgery, where rotation of the source-detector pair is limited to less than 180 degrees. Reconstruction of limited data with the conventional method proposed by Feldkamp, Davis and Kress (FDK) results in severe artifacts. Iterative methods may compensate for the lack of data by including additional prior information, although they imply a high computational burden and memory consumption.
PMID: 29764362
URI: https://hdl.handle.net/20.500.12530/36730
Rights: openAccess
Appears in Collections:Fundaciones e Institutos de Investigación > IIS H. General U. Gregorio Marañón > Artículos

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