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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qingyang Wei Tianyu Ma Yongjie Jin Yaqiang Liu Shi Wang Yilei Mao Shunda Du Junxiang Tong |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Liver Surgery, Peking Union Medical College Hospital, Beijing, China (Yilei Mao; Shunda Du; Junxiang Tong) || Department of Engineering Physics, Tsinghua University, Key Laboratory of Particle & Radiation Imaging, Ministry of Education, Beijing, China (Qingyang Wei; Tianyu Ma; Yongjie Jin; Yaqiang Liu; Shi Wang) |
| Abstract | Quantitative dynamic scintigraphic image studies provide in vivo measurements of dynamic physiological and biochemical processes in humans. Segmentation of scintigraphic images is one of the most important steps to distinguish organs of interest from the background. However, poor spatial resolution and signal-to-noise ratio (SNR) of scintigraphic images make accurate organ boundary segmentation difficult. In scintigraphic image studies, areas of specific binding are usually segmented by manually drawing regions of interest (ROIs), which is a time-consuming and subjective process. In this work, we describe a method to automatically segment 99mTc-GSA dynamic scintigraphic images based on the prior knowledge of drug metabolism, including the drug flow mechanism and the time of activity curves (TACs). Our results suggest that drug-metabolism-based segmentation can automatically segment tissues in dynamic scintigraphic images studies and has the potential to replace manual ROI segmentation for our application. |
| Starting Page | 203 |
| Ending Page | 207 |
| File Size | 1093287 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424464951 |
| e-ISBN | 9781424464982 |
| DOI | 10.1109/BMEI.2010.5639438 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-16 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Heart Drugs Image segmentation pTAC 99mTc-GSA Lungs Liver automatic image segmentation Manuals drug metabolism dynamic scintigraphic images Pixel |
| Content Type | Text |
| Resource Type | Article |
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