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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.
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Contributor : Jean-Louis Dillenseger <>
Submitted on : Monday, February 26, 2007 - 5:06:29 PM
Last modification on : Friday, January 15, 2021 - 3:33:12 AM
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  • HAL Id : inserm-00133031, version 1



Beatriz Sousa Santos, Jean-Louis Dillenseger. Quality Evaluation in Medical Visualization: some issues and a taxonomy of methods. Apr 2005, pp.612-620. ⟨inserm-00133031⟩



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