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Reference TypeConference Paper (Conference Proceedings)
Last Update2015: (UTC)
Metadata Last Update2020: (UTC) administrator
Citation KeyAssisSalvMascLeva:2015:PrPo
TitleDouble Noise Filtering in CT: Pre- and Post-Reconstruction
Access Date2021, Dec. 01
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Author1 Assis, Vinicius Covre de
2 Salvadeo, Denis Henrique Pinheiro
3 Mascarenhas, Nelson Delfino d'Ávila
4 Levada, Alexandre Luís Magalhães
Affiliation1 State University of São Paulo
2 State University of São Paulo
3 Faculdade Campo Limpo Paulista
4 Federal University of Sa ̃o Carlos
EditorPapa, João Paulo
Sander, Pedro Vieira
Marroquim, Ricardo Guerra
Farrell, Ryan
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador
DateAug. 26-29, 2015
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2015-06-19 16:09:01 :: -> administrator ::
2020-02-19 02:14:03 :: administrator -> :: 2015
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordscomputed tomography (CT)
double denoising
AbstractMotivated by the ALARA (As Low As Reasonably Achievable) principle, this paper proposes to denoise Computed Tomography (CT) images by using a double-filtering approach. First, projection data were filtered using methods to filter Poisson noise (pre-filtering step). Then the filtered backprojection (FBP) algorithm was applied to image reconstruction. After, the reconstructed images were denoised by using suitable methods for filtering Gaussian noise (post-filtering step). Finally, known metrics of image quality evaluation (such as SSIM and PSNR) were used to compare the filtered images with the ones considered ideal images in various combinations of filters. The results lead to the conclusion that a second filtering applied on image domain can improve the CT denoising quality from pre-filtering step. Thus, CT double-filtering strategy achieved a better balance between noise reduction and details preservation. > SDLA > SIBGRAPI 2015 > Double Noise Filtering...
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