# An analytical iterative statistical algorithm for image reconstruction from projections

International Journal of Applied Mathematics and Computer Science (2014)

- Volume: 24, Issue: 1, page 7-17
- ISSN: 1641-876X

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topRobert Cierniak. "An analytical iterative statistical algorithm for image reconstruction from projections." International Journal of Applied Mathematics and Computer Science 24.1 (2014): 7-17. <http://eudml.org/doc/271929>.

@article{RobertCierniak2014,

abstract = {The main purpose of the paper is to present a statistical model-based iterative approach to the problem of image reconstruction from projections. This originally formulated reconstruction algorithm is based on a maximum likelihood method with an objective adjusted to the probability distribution of measured signals obtained from an x-ray computed tomograph with parallel beam geometry. Various forms of objectives are tested. Experimental results show that an objective that is exactly tailored statistically yields the best results, and that the proposed reconstruction algorithm reconstructs an image with better quality than a conventional algorithm with convolution and back-projection.},

author = {Robert Cierniak},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {computed tomography; image reconstruction from projections; statistical reconstruction algorithm},

language = {eng},

number = {1},

pages = {7-17},

title = {An analytical iterative statistical algorithm for image reconstruction from projections},

url = {http://eudml.org/doc/271929},

volume = {24},

year = {2014},

}

TY - JOUR

AU - Robert Cierniak

TI - An analytical iterative statistical algorithm for image reconstruction from projections

JO - International Journal of Applied Mathematics and Computer Science

PY - 2014

VL - 24

IS - 1

SP - 7

EP - 17

AB - The main purpose of the paper is to present a statistical model-based iterative approach to the problem of image reconstruction from projections. This originally formulated reconstruction algorithm is based on a maximum likelihood method with an objective adjusted to the probability distribution of measured signals obtained from an x-ray computed tomograph with parallel beam geometry. Various forms of objectives are tested. Experimental results show that an objective that is exactly tailored statistically yields the best results, and that the proposed reconstruction algorithm reconstructs an image with better quality than a conventional algorithm with convolution and back-projection.

LA - eng

KW - computed tomography; image reconstruction from projections; statistical reconstruction algorithm

UR - http://eudml.org/doc/271929

ER -

## References

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