1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 6qtX3pFwXQZeBBx/w4RAD |
Repository | sid.inpe.br/banon/2002/11.05.10.52 |
Last Update | 2002:11.04.02.00.00 (UTC) administrator |
Metadata Repository | sid.inpe.br/banon/2002/11.05.10.53 |
Metadata Last Update | 2022:06.14.00.12.02 (UTC) administrator |
DOI | 10.1109/SIBGRA.2000.883897 |
Citation Key | MachadoCampGee:2000:PrInMa |
Title | Probabilistic intensity mapping in MRI image registration |
Year | 2000 |
Access Date | 2024, Sep. 20 |
Number of Files | 1 |
Size | 594 KiB |
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2. Context | |
Author | 1 Machado, Alexei Manso Corrêa 2 Campos, Mario Fernando Montenegro 3 Gee, James |
Editor | Carvalho, Paulo Cezar Pinto Walter, Marcelo |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI) |
Conference Location | Gramado, RS, Brazil |
Date | 17-20 Oct. 2000 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Pages | 74-81 |
Book Title | Proceedings |
Tertiary Type | Full Paper |
Organization | SBC - Brazilian Computer Society |
History (UTC) | 2008-07-17 14:10:49 :: administrator -> banon :: 2008-08-26 15:23:01 :: banon -> administrator :: 2009-08-13 20:36:52 :: administrator -> banon :: 2010-08-28 20:00:09 :: banon -> administrator :: 2022-06-14 00:12:02 :: administrator -> :: 2000 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | probability probabilistic intensity mapping MRI image registration MR sensors intensity distortions image registration likelihood modeling similarity metrics image matching morphological constraints noise experiments |
Abstract | In this work, we present a method which is able to relate different MR sensors with respect to intensity distortions in the output images. For the important problem of image registration, the method makes possible a principled approach to likelihood modeling or the construction of similarity metrics. Likelihood models can be used as prior knowledge of the relationship between intensities in both images, providing a fundamental information resource for image registration. A poor model of the intensity mapping for the image pair to be matched may lead to false matches, regardless of the prior morphological constraints assumed and will bias all subsequent analyses. A formal analysis of robustness under different kinds of noise is also provided and the findings compared to other relevant similarity metrics. Experiments are controlled based on the application of synthetic spatial and intensity deformations that guarantee a fiducial basis for comparison. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2000 > Probabilistic intensity mapping... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Probabilistic intensity mapping... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/6qtX3pFwXQZeBBx/w4RAD |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/w4RAD |
Target File | 74-81.pdf |
User Group | administrator |
Visibility | shown |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPEW34M/46PN6AP 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2022/04.27.03.08 20 sid.inpe.br/sibgrapi/2022/06.10.21.49 2 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Notes | The conference was held in Gramado, RS, Brazil, from October 17 to 20. |
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