A noise-insensitive hierarchical min-max octree for visualization of ultrasound datasets

Authors:
Sukhyun Lim;Kang-hee Seo;Byeong-Seok Shin
Affiliations:
Dept. Computer Science and Information Engineering, Inha University, Inchon, Rep. of Korea;Dept. Computer Science and Information Engineering, Inha University, Inchon, Rep. of Korea;Dept. Computer Science and Information Engineering, Inha University, Inchon, Rep. of Korea
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

There are two important factors to visualize ultrasound datasets for volume ray casting method. The first is an efficient method to skip over empty space and the second is an adequate noise filtering method. We propose a noise-insensitive hierarchical min-max octree. In preprocessing stage, we generate a filtered dataset and make a hierarchical min-max octree from the dataset. In rendering step, we exploit the hierarchical min-max octree only when rays skip over transparent region. If rays reach meaningful object, color and opacity values are computed from the original volume dataset. By adaptively using two datasets, our method increases image quality while reducing rendering time.