Abstract
As our ability to access the abundance of clinical data grows, it is imperative that methods to organize and to visualize this information be in place so as not to overwhelm users: increasingly, users are faced with information overload. Moreover, the manner of presentation is fundamental to how such information is interpreted, and can be the turning point in uncovering new insights and knowledge about a patient or a disease. And of course, medical imaging is itself an inherently visual medium. This chapter presents work related to the visualization of medical data, focusing on issues related to navigation and presentation by drawing upon imaging and other disciplines for examples of display and integration methods. We first cover different visual paradigms that have been developed (e.g., icons, graphs), grouped along dimensions that emphasize the different types of data relationships and workflow. Subsequently, issues related to combining these visualizations are given. As no single graphical user interface (GUI) can accommodate all users and the spectrum of tasks seen in the healthcare environment, the ultimate goal is to create an adaptive graphical interface that integrates clinical information so as to be conducive to a given user's objectives: efforts in this direction are discussed. Throughout, we describe applications that illustrate the many open issues revolving around medical data visualization.
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Notes
- 1.
In the model-view-controller (MVC) framework, although the organization of data (i.e., the model) helps drive how information is presented (i.e., the view), we leave that discussion to Chapter 7.
- 2.
A planar graph is a graph that can be drawn on a (2D) plane such that no edges cross. This problem has been well-studied in computer science and graph theory, with many linear-time algorithms for testing if a given graph is planar.
- 3.
Also referred to in the literature as subtraction images and difference images.
- 4.
Of course, too much layering of information can also be counterproductive and lead to overly complicated displays and/or data being obscured in the view. The KISS principle (keep it simple, stupid) should be followed in any design.
- 5.
The reader is referred to Chapter 3 for a more in-depth discussion of DICOM.
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Bui, A.A.T., Hsu, W. (2010). Medical Data Visualization: Toward Integrated Clinical Workstations. In: Bui, A., Taira, R. (eds) Medical Imaging Informatics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0385-3_4
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