Turkish Journal of Electrical Engineering and Computer Sciences




In volumetric path tracer, distance sampling and transmittance estimation techniques play a vital role in producing high-quality final rendered images. Previously, these techniques were implemented for production volume rendering, and were analyzed for faster convergence. In this article, we have augmented additional transmittance estimators including ratio tracking, residual ratio tracking and unbiased ray marcher in a GPU-based volumetric path tracer (Exposure Render) for biomedical datasets. We have also analyzed distance sampling methods and transmittance estimators perceptually using CIEDE2000 and Structural Similarity Index (SSIM). It was found that ratio and residual ratio tracking estimators performed close to each other and were better than unbiased ray marching perceptually. In addition, ray marching was observed to be better than delta tracking for distance sampling. We also validated these results by conducting a user study where different users were shown rendered images using varied distance samplers and transmittance estimators. Although, as expected, datasets had an impact on the rendering result for each technique, the perceptual differences did exist between distance samplers and transmittance estimators. As a major contribution of this work, we have found that distance sampling and transmittance estimation techniques have a crucial role for biomedical visualization due to having a direct impact on the final rendered image which is used in the diagnosis and prognosis of disease.


Monte Carlo, volume rendering, biomedical visualization

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