Shader Based Volumetric Path Tracing of Medical Data

16.03.2025, Abschlussarbeiten, Bachelor- und Masterarbeiten

This project aims to enable path tracing of volumetric medical data, such as CT scans, within the Unity game engine. The resulting library will support researchers in developing high-fidelity, real-time medical visualizations to advance medical research.

The Human-Centered Computing and Extended Reality Lab of the Professorship for Machine Intelligence in Orthopedics seeks applicants for Bachelor/Master Thesis for the Summer Semester 2025.

Project Description

The objective of this project is to integrate full volumetric path tracing into the Unity game engine. As a starting point, a partial path tracer and file-loading implementation based on publicly available rendering code is available. The final implementation should seamlessly integrate with Unity’s scene structure.
Key research and development areas include:

• Enhancing the correctness of the existing path tracer
• Optimizing performance for real-time rendering
• Implementing advanced rendering features, such as specularity and depth of field
• Integrating denoising techniques
• Exploring stereoscopic visualization for mixed reality applications
• Investigating state-of-the-art volumetric path tracing methods

Recommended background (or motivation in learning):

• Proficiency in C, C++, and C#
• Experience with HLSL shader programming
• Knowledge of OpenGL
• Familiarity with the Unity game engine
• Understanding of computer graphics principles

Please send your transcript of records, CV and motivation to: Constantin Kleinbeck (constantin.kleinbeck@tum.de) with CC to hex-thesis.ortho@mh.tum.de

Literatur

[1] N. Hofmann, J. Martschinke, K. Engel, and M. Stamminger, “Neural Denoising for Path Tracing of Medical Volumetric Data,” Proc. ACM Comput. Graph. Interact. Tech., vol. 3, no. 2, pp. 1–18, Aug. 2020, doi: 10.1145/3406181.
[2] J. A. Iglesias-Guitian, P. Mane, and B. Moon, “Real-Time Denoising of Volumetric Path Tracing for Direct Volume Rendering,” IEEE Trans. Visual. Comput. Graphics, vol. 28, no. 7, pp. 2734–2747, Jul. 2022, doi: 10.1109/TVCG.2020.3037680.
[3] D. Comaniciu, K. Engel, B. Georgescu, and T. Mansi, “Shaping the future through innovations: From medical imaging to precision medicine,” Medical Image Analysis, vol. 33, pp. 19–26, Oct. 2016, doi: 10.1016/j.media.2016.06.016.
[4] T. Kroes, F. H. Post, and C. P. Botha, “Exposure Render: An Interactive Photo-Realistic Volume Rendering Framework,” PLOS ONE, vol. 7, no. 7, p. e38586, Jul. 2012, doi: 10.1371/journal.pone.0038586.
[5] P. Ljung, J. Krüger, E. Groller, M. Hadwiger, C. D. Hansen, and A. Ynnerman, “State of the Art in Transfer Functions for Direct Volume Rendering,” Computer Graphics Forum, vol. 35, no. 3, pp. 669–691, 2016, doi: 10.1111/cgf.12934.

Kontakt: hex-thesis.ortho@mh.tum.de, constantin.kleinbeck@tum.de