Information visualization and its application to medicine

doi:10.1016/S0933-3657(00)00101-9

Artificial Intelligence in Medicine

Volume 22, Issue 2, May 2001, Pages 81-88

https://doi.org/10.1016/S0933-3657(00)00101-9 Get rights and content

Abstract

This paper provides an introduction to the field of information visualization (IV) and a discussion of its application to medical systems. More specifically, it aims at: (i) defining what IV is and what are its goals (ii) highlighting the similarities and differences between IV and traditional medical imaging (iii) illustrating the potential of IV for medical applications by examining several examples of implemented systems and (iv) giving some general indications about the purposes and the effective exploitation of an IV component into a medical system.

Introduction

The amount and the complexity of data available at clinicians’ fingertips are constantly increasing as a result of technology advancements in computer performance and storage capacity. Unfortunately, due to well-known cognitive and perceptual limitations, the quantity of information a user can examine and handle at a given instant is very limited. Therefore, the various members of the clinical staff (physicians, technicians, nurses, students, managers) will not be able to take advantage of these increasingly large amounts of data and will also incur the risk of being overwhelmed by them, if computer applications do not take adequately into account effective presentation and interaction with data. Answers to these problems are a central theme of study and development in the rapidly growing area of information visualization (IV).

IV can thus play an important role in the development of most kinds of medical systems, and the purpose of this paper is both to provide an introduction to the field of IV and to highlight its importance in medical applications. First, we will define more precisely what IV is, what are its goals, and what are the kinds of data it operates on. Then, we will concentrate on IV for medical data, also illustrating significant case studies in different categories. The concluding section contains some remarks about the effective exploitation of IV in medical systems.

Section snippets

Information visualization: definition, goals and taxonomy

Visualization is generally defined as “the act or process of interpreting in visual terms or of putting into visible form” [11]. Information visualization can be defined as “the process of transforming data, information, and knowledge into visual form making use of humans’ natural visual capabilities” [7] or, more concisely, as “the computer-assisted use of visual processing to gain understanding” [1].

IV aims at reducing the complexity of the examination and understanding of information for

Visualizing medical data

Interest in visualization for medical applications has a long tradition in the field of medical imaging. However, it must be pointed out that the scope of this interest has been narrower than the broad definition and illustration of IV given in the previous section. Medical imaging is more concentrated on problems such as image acquisition (e.g. by means of tomography scans) and the processing needed to visualize the acquired images (i.e. a large number of different techniques ranging from

Final remarks

In spite of the growing number of IV techniques in use in medical applications, a word of caution is needed for the developer who wants to add an IV component to his/her system: since only a few tested guidelines exist [18], and no disciplined design methodologies and engineering principles have been yet identified, special care is needed in order to obtain an effective design.

For example, in contrast to most medical imaging data, IV focuses also on abstract information which cannot be

Acknowledgements

I would like to thank Carlo Combi for his feedback on the preliminary version of this paper.

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Information visualization and its application to medicine

Abstract

Introduction

Section snippets

Information visualization: definition, goals and taxonomy

Visualizing medical data

Final remarks

Acknowledgements

Artif. Intell. Med.

Artif. Intell. Med.

Artif. Intell. Med.

Artif. Intell. Med.

Information visualization

ACM Interactions

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IEEE Comput.

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