@conference{fd5f223ea38a4867a10fb963fb743301,
title = "Hemodynamics segregation using expectation-maximization algorithm initialized by hierarchical clustering on MR dynamic images from patients with unilateral internal carotid artery stenosis: World Congress on Medical Physics and Biomedical Engineering: Diagnostic Imaging",
abstract = "Expectation-maximization (EM) algorithm initialized by hierarchical clustering (HC) was applied on dynamic susceptibility contrast (DSC) MR images from the patients with unilateral internal carotid artery stenosis to segment out different brain tissue clusters depending on their own specific blood supply patterns. In comparison with the segmented normal and abnormal gray matter components demonstrated that difference in mean transit time (dMTT) and difference in time to peak (dTTP) can robustly reveal the hemodynamic change from pre-stenting to post-stenting state (p-values are 0.027 and 0.004, respectively). Additionally, change of local deficit before and after the placement of stent can be further investigated by the ratio of numbers of normal to abnormal gray-matter pixels within the territories of anterior cerebral artery (ACA), middle cerebral artery (MCA) and posterior cerebral artery (PCA) (p-values are 0.375, 0.037 and 0.020, respectively) in assistance to diagnosis and therapeutic assessment. {\textcopyright} 2009 Springer-Verlag.",
keywords = "Anterior cerebral artery, Before and after, Blood supply, Brain tissue, Cerebral arteries, Dynamic images, Expectation-maximization algorithms, Gray matter, Hemodynamic changes, Hierarchical Clustering, Internal carotid artery, Mean transit time, Middle cerebral artery, MR images, ON dynamics, P-values, Stenting, Time to peak, Biomedical engineering, Blind source separation, Clustering algorithms, Dynamics, Hemodynamics, Hydrodynamics, Image segmentation, Magnetic susceptibility, Maximum principle, Optimization, Physics, Medical imaging",
author = "Yu-Te Wu and Chia-Feng Lu and Shang-Ran Huang and Feng-Chi Chang and Wan-Yuo Guo",
note = "會議代碼: 81644 Export Date: 31 March 2016 通訊地址: Wu, Y.-T.; Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, No.155, Sec.2, Linong Street, Taipei, Taiwan; 電子郵件： ytwu@ym.edu.tw 參考文獻: Zierler, K.L., Theoretical basis of indicatordilution methods for measuring flow and volume (1962) Circulation Research, 10, pp. 393-407; Ostergaard, L., Weisskoff, R.M., Chesler, D.A., High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis (1996) Magn Reson Med, 36 (5), pp. 715-725; Wu, Y.T., Chou, Y.C., Lu, C.F., Tissue classification from brain perfusion MR images using expectation-maximization algorithm initialized by hierarchical clustering on whitened data (2008) 13th ICBME, Singapore, 2008, pp. 714-717; Wu, O., {\O}stergaard, L., Weisskoff, R.M., Tracer arrival timing-insensitive technique or estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix (2003) Magn. Reson. Med., 50, pp. 100-110; Mai, J.K., Assheuer, J., Paxinos, G., (1997) Atlas of the Human Brain, pp. 33-35. , Academic Press",
year = "2009",
doi = "10.1007/978-3-642-03879-2-262",
language = "English",
pages = "936--939",
}