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Content Provider | IEEE Xplore Digital Library |
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Author | Khurshid, K. Berger, K.L. McGough, R.J. |
Copyright Year | 2009 |
Abstract | Computed Tomography (CT) is used for the attenuation correction of Positron Emission Tomography (PET) to enhance the efficiency of data acquisition process and to improve the quality of the reconstructed PET data in the brain. Due to the use of two different modalities, chances of misalignment between PET and CT images are quite significant. The main cause of this misregistration is the motion of the patient during the PET scan and between the PET and CT scans. This misalignment produces an erroneous CT attenuation map that can project the bone and water attenuation parameters onto the brain, thereby under- or over-estimating the attenuation. To avoid the misregistration artifact and potential diagnostic misinterpretation, automated software for PET/CT brain registration has been developed. This software extracts the brain surface information from the CT and PET images and compensates for the translational and rotational misalignment between the two scans. This procedure has been applied to the dataset of a patient with visible perfusion defect in the brain, and the results show that the CTAC produced after the image registration eliminates that hypoperfusion artifact caused by the erroneous attenuation of the PET images. |
Starting Page | 5805 |
Ending Page | 5808 |
File Size | 542152 |
Page Count | 4 |
File Format | |
ISBN | 9781424432967 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2009.5335188 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2009-09-03 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Positron emission tomography Attenuation Computed tomography Brain Image segmentation Image reconstruction USA Councils Data acquisition Bones Data mining segmentation Misregistration PET CT attenuation correction |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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