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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mehrabian, H. Pang, I. Chopra, R. Martel, A.L. |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada (Mehrabian, H.; Pang, I.; Chopra, R.; Martel, A.L.) |
| Abstract | Pharmacokinetic (PK) modeling of tumors provides information about perfusion and vascular permeability of tumors. Identifying arterial input function (AIF) is crucial in PK modeling using dynamic contrast enhanced (DCE)-MRI. An adaptive complex independent component analysis method is developed to identify and separate AIF from complex DCE-MRI data. The results are compared with a previously introduced AIF estimation method that applied ICA to magnitude DCE-MRI data. Using simulation and experimental phantom studies it is shown that using both magnitude and phase data (complex) results in a more robust and more accurate AIF measurement algorithm. |
| Starting Page | 1052 |
| Ending Page | 1055 |
| File Size | 607920 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457718571 |
| ISSN | 19457928 |
| e-ISBN | 9781457718588 |
| DOI | 10.1109/ISBI.2012.6235739 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-02 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Tumors Image resolution Phantoms Electron tubes Magnetic resonance imaging Adaptation models Arterial Input Function (AIF) Adaptive Complex ICA (AC-ICA) Pharmacokinetic modeling |
| Content Type | Text |
| Resource Type | Article |
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