Sparsity-Based Deconvolution of Low-Dose Perfusion CT Using Learned Dictionaries
Computational tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, such as stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a novel sparsity-base deconvolution method to estimate cerebral blood flow in CTP performed at low-dose. We first built an overcomplete dictionary from high-dose perfusion maps and then performed deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on a clinical dataset of ischemic patients. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain.
KeywordsCerebral Blood Flow Sparse Code Compute Tomography Perfusion Perfusion Parameter Learn Dictionary
- 4.Mouridsen, K., Friston, K., Hjort, N., Gyldensted, L., Ostergaard, L., Kiebel, S.: Bayesian estimation of cerebral perfusion using a physiological model of microvasculature. Neuro Image 33, 570–579 (2006)Google Scholar
- 7.Fang, R., Chen, T., Sanelli, P.C.: Sparsity-Based Deconvolution of Low-dose Brain Perfusion CT in Subarachnoid Hemorrhage Patients. In: IEEE Proceedings of the Ninth International Symposium on Biomedical Imaging (2012)Google Scholar
- 8.Fang, R., Raj, A., Chen, T., Sanelli, P.C.: Radiation Dose Reduction In Computed Tomography Perfusion Using Spatial-Temporal Bayesian Methods. In: Pelc, N.J., Nishikawa, R.M., Whiting, B.R. (eds.) Medical Imaging. SPIE, vol. 8313, pp. 45–53 (2012)Google Scholar
- 9.Elad, M., Aharon, M.: Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries. IEEE Transactions on Image Processing 15(12) (2006)Google Scholar
- 11.Britten, A., Crotty, M., Kiremidjian, H., Grundy, A., Adam, E.: The Addition of Computer Simulated Noise to Investigate Radiation Dose and Image Quality in Images with Spatial Correlation of Statistical Noise: An Example Application to X-Ray CT of the Brain. British Journal of Radiology 77(916), 323 (2004)CrossRefGoogle Scholar