Iterative High Resolution Tomography from Combined High-Low Resolution Sinogram Pairs
(2018) 19th International Workshop on Combinatorial Image Analysis, IWCIA 2018 In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11255 LNCS. p.150-163- Abstract
In some cases of tomography we can only gain high resolution projections of the object with only partial coverage, whereas only a small part of the object – a given Region of Interest (ROI) – is fully covered by high resolution projections. In such cases the structures outside the region of interest cause artefacts to appear in the reconstructed image and degrade the image quality of the tomogram. We proposed three new iterative approaches for the accurate reconstruction of the ROI by combining a high resolution set of projections, with low resolution full field of view projections and prior information. We also evaluate our methods reconstructing software phantoms, and compare their performance to other methods in the literature.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/6bcddc0b-7c5c-4f5b-8e61-7e97f4ba4ba5
- author
- Varga, László and Mokso, Rajmund LU
- organization
- publishing date
- 2018
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- GPGPU, Reconstruction, Region of interest, ROI, Sinogram combination, Tomography
- host publication
- Combinatorial Image Analysis - 19th International Workshop, IWCIA 2018, Proceedings
- series title
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- editor
- Barneva, Reneta P. ; Tavares, João Manuel R.S and Brimkov, Valentin E.
- volume
- 11255 LNCS
- pages
- 14 pages
- publisher
- Springer
- conference name
- 19th International Workshop on Combinatorial Image Analysis, IWCIA 2018
- conference location
- Porto, Portugal
- conference dates
- 2018-11-22 - 2018-11-24
- external identifiers
-
- scopus:85057403786
- ISSN
- 1611-3349
- 0302-9743
- ISBN
- 9783030052874
- DOI
- 10.1007/978-3-030-05288-1_12
- language
- English
- LU publication?
- yes
- id
- 6bcddc0b-7c5c-4f5b-8e61-7e97f4ba4ba5
- date added to LUP
- 2018-12-10 11:08:26
- date last changed
- 2024-06-11 00:25:43
@inproceedings{6bcddc0b-7c5c-4f5b-8e61-7e97f4ba4ba5, abstract = {{<p>In some cases of tomography we can only gain high resolution projections of the object with only partial coverage, whereas only a small part of the object – a given Region of Interest (ROI) – is fully covered by high resolution projections. In such cases the structures outside the region of interest cause artefacts to appear in the reconstructed image and degrade the image quality of the tomogram. We proposed three new iterative approaches for the accurate reconstruction of the ROI by combining a high resolution set of projections, with low resolution full field of view projections and prior information. We also evaluate our methods reconstructing software phantoms, and compare their performance to other methods in the literature.</p>}}, author = {{Varga, László and Mokso, Rajmund}}, booktitle = {{Combinatorial Image Analysis - 19th International Workshop, IWCIA 2018, Proceedings}}, editor = {{Barneva, Reneta P. and Tavares, João Manuel R.S and Brimkov, Valentin E.}}, isbn = {{9783030052874}}, issn = {{1611-3349}}, keywords = {{GPGPU; Reconstruction; Region of interest; ROI; Sinogram combination; Tomography}}, language = {{eng}}, pages = {{150--163}}, publisher = {{Springer}}, series = {{Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}}, title = {{Iterative High Resolution Tomography from Combined High-Low Resolution Sinogram Pairs}}, url = {{http://dx.doi.org/10.1007/978-3-030-05288-1_12}}, doi = {{10.1007/978-3-030-05288-1_12}}, volume = {{11255 LNCS}}, year = {{2018}}, }