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

Yu-Te Wu, Chia-Feng Lu, Shang-Ran Huang, Feng-Chi Chang, Wan-Yuo Guo

Research output: Contribution to conferenceOther

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. © 2009 Springer-Verlag.
Original languageEnglish
Pages936-939
Number of pages4
DOIs
Publication statusPublished - 2009
Externally publishedYes

Fingerprint

Biomedical Engineering
Carotid Stenosis
Physics
Diagnostic Imaging
Cluster Analysis
Hemodynamics
Posterior Cerebral Artery
Anterior Cerebral Artery
Middle Cerebral Artery
Stents
Brain
Gray Matter
Therapeutics

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

Cite this

@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. {\circledC} 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",

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T1 - Hemodynamics segregation using expectation-maximization algorithm initialized by hierarchical clustering on MR dynamic images from patients with unilateral internal carotid artery stenosis

T2 - World Congress on Medical Physics and Biomedical Engineering: Diagnostic Imaging

AU - Wu, Yu-Te

AU - Lu, Chia-Feng

AU - Huang, Shang-Ran

AU - Chang, Feng-Chi

AU - Guo, Wan-Yuo

N1 - 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., Østergaard, 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

PY - 2009

Y1 - 2009

N2 - 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. © 2009 Springer-Verlag.

AB - 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. © 2009 Springer-Verlag.

KW - Anterior cerebral artery

KW - Before and after

KW - Blood supply

KW - Brain tissue

KW - Cerebral arteries

KW - Dynamic images

KW - Expectation-maximization algorithms

KW - Gray matter

KW - Hemodynamic changes

KW - Hierarchical Clustering

KW - Internal carotid artery

KW - Mean transit time

KW - Middle cerebral artery

KW - MR images

KW - ON dynamics

KW - P-values

KW - Stenting

KW - Time to peak

KW - Biomedical engineering

KW - Blind source separation

KW - Clustering algorithms

KW - Dynamics

KW - Hemodynamics

KW - Hydrodynamics

KW - Image segmentation

KW - Magnetic susceptibility

KW - Maximum principle

KW - Optimization

KW - Physics

KW - Medical imaging

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U2 - 10.1007/978-3-642-03879-2-262

DO - 10.1007/978-3-642-03879-2-262

M3 - Other

SP - 936

EP - 939

ER -