JOURNAL ARTICLE

Visibility guided multimodal volume visualization

Abstract

With the advances in dual medical imaging, the requirements for multimodal and multifield volume visualization begin to emerge. One of the challenges in multimodal visualization is how to simplify the process of generating informative pictures from complementary data. In this paper we present an automatic technique that makes use of dual modality information, such as CT and PET, to produce effective focus+context volume visualization. With volume ray casting, per-ray visibility histograms summarize the contribution of samples along each ray to the final image. By quantifying visibility for the region of interest, indicated by the PET data, occluding tissues can be made just transparent enough to give a clear view of the features in that region while preserving some context. Unlike most previous methods relying on costly-preprocessing and tedious manual tuning, our technique achieves comparable and better results based on on-the-fly processing that still enables interactive visualization. Our work thus offers a powerful visualization technique for examining multimodal volume data. We demonstrate the technique with scenarios for the detection and diagnosis of cancer and other pathologies.

Keywords:
Visualization Computer science Visibility Preprocessor Context (archaeology) Artificial intelligence Volume (thermodynamics) Computer vision Data visualization Ray casting Volume rendering Histogram Modality (human–computer interaction) Image (mathematics)

Metrics

2
Cited By
0.61
FWCI (Field Weighted Citation Impact)
35
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Computer Graphics and Visualization Techniques
Physical Sciences →  Computer Science →  Computer Graphics and Computer-Aided Design
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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