Slice-based ray casting volume shadow of volumetric datasets

Dening Luo; Weixiang Ma; Dequan Guo

doi:10.1117/12.3029429

13 May 2024 Slice-based ray casting volume shadow of volumetric datasets

Dening Luo, Weixiang Ma, Dequan Guo

Proceedings Volume 13158, Seventh International Conference on Computer Graphics and Virtuality (ICCGV 2024); 1315803 (2024) https://doi.org/10.1117/12.3029429
Event: Seventh International Conference on Computer Graphics and Virtuality (ICCGV24), 2024, Hangzhou, China

Abstract

The realistic volume shadow of volumetric datasets can improve the perception of shape and depth, and further enhance the efficiency of detecting defects, anomalies, and other issues. In this paper, a novel and high-performance method called slice-based ray casting (SBRC) is proposed to implement the volume shadow of volumetric datasets. The first step of the SBRC method is to use the light source as the viewpoint to render the illumination information of each slice of the volumetric datasets, slice by slice, into the illumination attenuation buffer. The second step is to use the camera as the viewpoint, render volumetric datasets using ray casting, and calculate volume shadows using the illumination attenuation buffer. The experiments show that the method can obtain much better volume shadows and more scalable performance than other volume illumination methods. This is due to the illumination attenuation calculation slice by slice and the high-efficiency shadow calculation in ray casting. And, by using a genetic algorithm, we can optimize the shadow calculation parameters in CT images to make the edges in the images clearer.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dening Luo, Weixiang Ma, and Dequan Guo "Slice-based ray casting volume shadow of volumetric datasets", Proc. SPIE 13158, Seventh International Conference on Computer Graphics and Virtuality (ICCGV 2024), 1315803 (13 May 2024); https://doi.org/10.1117/12.3029429

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