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

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.