Paper Info
Title
Quality Evaluation in Medical Visualization: some issues and a taxonomy of methods
Abstract
Among the several medical imaging stages (acquisition, reconstruction, etc.), visualization is the latest stage on which decision is generally taken. Scientific visualization tools allow to process complex data into a graphical visible and understandable form, the goal being to provide new insight. If the evaluation of procedures is a crucial issue and a main concern in medicine, paradoxically visualization techniques, predominantly in tri-dimensional imaging, have not been the subject of many evaluation studies. This is perhaps due to the fact that the visualization process integrates the Human Visual and Cognitive Systems, which makes evaluation especially difficult. However, as in medical imaging, the question of quality evaluation of a specific visualization remains a main challenge. While a few studies concerning specific cases have already been published, there is still a great need for definition and systemization of evaluation methodologies. The goal of our study is to propose such a framework, which makes it possible to take into account all the parameters taking part in the evaluation of a visualization technique. Concerning the problem of quality evaluation in data visualization in general, and in medical data visualization in particular, three different concepts appear to be fundamental: the type and level of components used to convey to the user the information contained in the data, the type and level at which evaluation can be performed, and the methodologies used to perform such evaluation. We propose a taxonomy involving types of methods that can be used to perform evaluation at different levels.
Year
DOI
Venue
2005
10.1117/12.594549
PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Keywords
Field
DocType
quantitative evaluation,medical data visualization,taxonomy
Data science,Data visualization,Information visualization,Medical imaging,Computer science,Visualization,Visual analytics,Complex data type,Scientific visualization,Creative visualization
Conference
Volume
ISSN
Citations 
5744
0277-786X
0
PageRank 
References 
Authors
0.34
33
2
Name
Order
Citations
PageRank
Beatriz Sousa Santos137445.01
Jean-Louis Dillenseger210912.96