Skip to Main content Skip to Navigation
Journal articles

An automated image-processing strategy to analyze dynamic arterial spin labeling perfusion studies. Application to human skeletal muscle under stress.

Abstract : Arterial spin labeling (ASL) perfusion measurements allow the follow-up of muscle perfusion with high temporal resolution during a stress test. Automated image processing is proposed to estimate perfusion maps from ASL images. It is based on two successive analyses: at first, automated rejection of the image pairs between which a large displacement is detected is performed, followed by factor analysis of the dynamic data and cluster analysis to classify pixels with large signal variation characteristic of vessels. Then, after masking these "vascular" pixels, factor analysis and cluster analysis are further applied to separate the different muscles between low or high perfusion increase, yielding a functional map of the leg. Data from 10 subjects (five normal volunteers and five elite sportsmen) had been analyzed. Resulting time perfusion curves from a region of interest (ROI) in active muscles show a good accordance whether extracted with automated processing or with manual processing. This method of functional segmentation allows automated suppression of vessels and fast visualization of muscles with high, medium or low perfusion, without any a priori knowledge.
Document type :
Journal articles
Complete list of metadatas

https://www.hal.inserm.fr/inserm-00163717
Contributor : Vanessa Saidi <>
Submitted on : Wednesday, July 18, 2007 - 11:18:42 AM
Last modification on : Thursday, August 20, 2020 - 12:52:03 PM

Identifiers

Citation

Frédérique Frouin, Sandrine Duteil, David Lesage, Pierre Carlier, Alain Herment, et al.. An automated image-processing strategy to analyze dynamic arterial spin labeling perfusion studies. Application to human skeletal muscle under stress.. Magnetic Resonance Imaging, Elsevier, 2006, 24 (7), pp.941-51. ⟨10.1016/j.mri.2005.09.012⟩. ⟨inserm-00163717⟩

Share

Metrics

Record views

301