A faster ordered-subset convex algorithm for iterative reconstruction in a rotation-free micro-CT system
We present a faster iterative reconstruction algorithm based on the ordered-subset convex (OSC) algorithm for transmission CT. The OSC algorithm was modified such that it calculates the normalization term before the iterative process in order to save computational cost. The modified version requires...
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| Veröffentlicht in: | Physics in medicine & biology 2009-02, Vol.54 (4), p.1061-1072 |
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| container_title | Physics in medicine & biology |
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| creator | Quan, E Lalush, D S |
| description | We present a faster iterative reconstruction algorithm based on the ordered-subset convex (OSC) algorithm for transmission CT. The OSC algorithm was modified such that it calculates the normalization term before the iterative process in order to save computational cost. The modified version requires only one backprojection per iteration as compared to two required for the original OSC. We applied the modified OSC (MOSC) algorithm to a rotation-free micro-CT system that we proposed previously, observed its performance, and compared with the OSC algorithm for 3D cone-beam reconstruction. Measurements on the reconstructed images as well as the point spread functions show that MOSC is quite similar to OSC; in noise-resolution trade-off, MOSC is comparable with OSC in a regular-noise situation and it is slightly worse than OSC in an extremely high-noise situation. The timing record shows that MOSC saves 25-30% CPU time, depending on the number of iterations used. We conclude that the MOSC algorithm is more efficient than OSC and provides comparable images. |
| doi_str_mv | 10.1088/0031-9155/54/4/016 |
| format | Article |
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We conclude that the MOSC algorithm is more efficient than OSC and provides comparable images.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Phantoms, Imaging</subject><subject>Radiographic Image Enhancement - methods</subject><subject>Radiographic Image Interpretation, Computer-Assisted - methods</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Tomography, X-Ray Computed - methods</subject><issn>0031-9155</issn><issn>1361-6560</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkM9LwzAUgIMobk7_AQ-Sk-AhLmnStDmO4S8YeJnnkLavLtI2NUmH--_t2NCDF0-PB9_7eHwIXTN6z2iezynljCiWpvNUzMWcMnmCpoxLRmQq6Sma_gATdBHCB6WM5Yk4RxOmmMwVl1O0WeDahAgeO1-Bh4qEoQgQcem6LXxh07w7b-OmxbXz2I6giXYL2MMIhOiHMlrXYdthg72LZr-R2gPg1pbekeUah93oby_RWW2aAFfHOUNvjw_r5TNZvT69LBcrUvKMRyJVqShNuBJJSqWSsqJpkVdGZLXkApgQXBmaV8pUuckKWhQlsFIYAVLVPJN8hm4P3t67zwFC1K0NJTSN6cANQUuZpyqRdASTAzi-GYKHWvfetsbvNKN631fv8-l9Pp0KLfTYdzy6OdqHooXq9-QYdATIAbCu_5_w7i__l9N9VfNv9cqREg</recordid><startdate>20090221</startdate><enddate>20090221</enddate><creator>Quan, E</creator><creator>Lalush, D S</creator><general>IOP Publishing</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20090221</creationdate><title>A faster ordered-subset convex algorithm for iterative reconstruction in a rotation-free micro-CT system</title><author>Quan, E ; Lalush, D S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c373t-69c90023942506966d05b8da47f634e14439a08d9ad8a7b0bbce1c4a4e69f3763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Phantoms, Imaging</topic><topic>Radiographic Image Enhancement - methods</topic><topic>Radiographic Image Interpretation, Computer-Assisted - methods</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Tomography, X-Ray Computed - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Quan, E</creatorcontrib><creatorcontrib>Lalush, D S</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Physics in medicine & biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Quan, E</au><au>Lalush, D S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A faster ordered-subset convex algorithm for iterative reconstruction in a rotation-free micro-CT system</atitle><jtitle>Physics in medicine & biology</jtitle><addtitle>Phys Med Biol</addtitle><date>2009-02-21</date><risdate>2009</risdate><volume>54</volume><issue>4</issue><spage>1061</spage><epage>1072</epage><pages>1061-1072</pages><issn>0031-9155</issn><eissn>1361-6560</eissn><abstract>We present a faster iterative reconstruction algorithm based on the ordered-subset convex (OSC) algorithm for transmission CT. 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| source | MEDLINE; Institute of Physics Journals |
| subjects | Algorithms Artificial Intelligence Imaging, Three-Dimensional - methods Pattern Recognition, Automated - methods Phantoms, Imaging Radiographic Image Enhancement - methods Radiographic Image Interpretation, Computer-Assisted - methods Reproducibility of Results Sensitivity and Specificity Tomography, X-Ray Computed - methods |
| title | A faster ordered-subset convex algorithm for iterative reconstruction in a rotation-free micro-CT system |
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