Visual analysis of cerebral perfusion data -- four interactive approaches and a comparison

Steffen Oeltze, Bernhard Preim, Helwig Hauser, Jarle Rørvik, Arvid Lundervold

INPROCEEDINGS, Proceedings of the 6th Intern. Symp. on Image and Signal Processing and Analysis (ISPA 2009), Sept., 2009

Abstract

Cerebral perfusion data are acquired to characterize the regional blood supply of brain tissue. One of their major diagnostic applications is ischemic stroke assessment. We present a comparison of four interactive approaches to analyzing cerebral perfusion data from ischemic stroke patients which are based on (1) concentration-time curves (CTC) derived from the original data, (2) parameters describing the CTC shape, (3) enhancement trends computed in a statistical analysis, and (4) semi-quantitative perfusion parameters derived via parametric modelling and deconvolution. The comparison is carried out with regard to the involved data pre-processing, the complexity of the interactive analysis and the resulting tissue selections. It is supported by a visual analysis framework that integrates the different approaches. The rich information content in time-dependent 3D perfusion data is both an opportunity for improved diagnosis and a challenge how to optimize the assessment of such rich data. With our comparison we contribute to a discussion between data-near and model-near assessment strategies and their respective opportunities.

Published

Proceedings of the 6th Intern. Symp. on Image and Signal Processing and Analysis (ISPA 2009)

• Pages: 582–589
• Date: Sept. 2009

Media

BibTeX

@InProceedings{oeltze09perfusion,
title={Visual analysis of cerebral perfusion data -- four interactive approaches 
	and a comparison},
author={Steffen Oeltze and Bernhard Preim and Helwig Hauser and 
	Jarle R{\o}rvik and Arvid Lundervold},
booktitle={Proceedings of the 6th Intern. Symp. on Image and Signal Processing and Analysis (ISPA 2009)},
year={2009},
month={Sept.},
pages={582--589},
abstract = {Cerebral perfusion data are acquired to characterize the regional 
blood supply of brain tissue. One of their major diagnostic applications is ischemic
stroke assessment. We present a comparison of four interactive approaches to analyzing
cerebral perfusion data from ischemic stroke patients which are based on 
(1) concentration-time curves (CTC) derived from the original data, (2) parameters 
describing the CTC shape, (3) enhancement trends computed in a statistical analysis, 
and (4) semi-quantitative perfusion parameters derived via parametric modelling and 
deconvolution. The comparison is carried out with regard to the involved data 
pre-processing, the complexity of the interactive analysis and the resulting tissue 
selections. It is supported by a visual analysis framework that integrates the 
different approaches. The rich information content in time-dependent 3D perfusion data 
is both an opportunity for improved diagnosis and a challenge how to optimize the 
assessment of such rich data. With our comparison we contribute to a discussion 
between data-near and model-near assessment strategies and their respective opportunities.},


}