A Review of Three-Dimensional Medical Image Visualization

Author:

Zhou Liang1,Fan Mengjie1,Hansen Charles2,Johnson Chris R.2,Weiskopf Daniel3

Affiliation:

1. National Institute of Health Data Science, Peking University, Beijing, China

2. Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA

3. Visualization Research Center (VISUS), University of Stuttgart, Stuttgart, Germany

Abstract

Importance . Medical images are essential for modern medicine and an important research subject in visualization. However, medical experts are often not aware of the many advanced three-dimensional (3D) medical image visualization techniques that could increase their capabilities in data analysis and assist the decision-making process for specific medical problems. Our paper provides a review of 3D visualization techniques for medical images, intending to bridge the gap between medical experts and visualization researchers. Highlights . Fundamental visualization techniques are revisited for various medical imaging modalities, from computational tomography to diffusion tensor imaging, featuring techniques that enhance spatial perception, which is critical for medical practices. The state-of-the-art of medical visualization is reviewed based on a procedure-oriented classification of medical problems for studies of individuals and populations. This paper summarizes free software tools for different modalities of medical images designed for various purposes, including visualization, analysis, and segmentation, and it provides respective Internet links. Conclusions . Visualization techniques are a useful tool for medical experts to tackle specific medical problems in their daily work. Our review provides a quick reference to such techniques given the medical problem and modalities of associated medical images. We summarize fundamental techniques and readily available visualization tools to help medical experts to better understand and utilize medical imaging data. This paper could contribute to the joint effort of the medical and visualization communities to advance precision medicine.

Funder

National Institutes of Health

Data for Better Health Project of Peking University-Master Kong

Publisher

American Association for the Advancement of Science (AAAS)

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