Semantic Cinematic Volume Rendering with Monte Carlo Path Tracing
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Solution Overview
Problem
Cinematic volume rendering technologies, based on path tracing, currently ignore semantic information that could enhance image quality and clinical utility in medical imaging, such as tissue type classification and lesion detection, limiting their application in medical diagnostics.
Innovation Solution
Integration of semantic information into the cinematic volume rendering process using volumetric Monte-Carlo path tracing, where scan data is processed to extract material properties, surface characteristics, and illumination models, allowing for anatomy-specific renderings and feature maps that highlight clinical features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional volumetric Monte-Carlo path tracing is used for cinematic volume rendering, then image quality with noise suppression and structure enhancement is improved, but semantic information from medical images is lost or ignored
Solution Approach 1:
The patent applies segmentation by dividing the volume rendering process into two distinct phases: (1) cinematic volume rendering using volumetric Monte-Carlo path tracing to generate high-quality images with noise suppression, and (2) extraction of semantic information from the rendered images or original scan data. This segmentation allows both high-quality visualization and preservation of semantic information to coexist by processing them as separate but complementary outputs.
Solution Approach 2:
The patent merges cinematic volume rendering with semantic information extraction by integrating both processes within a unified system architecture. The server performs both the computationally intensive path tracing rendering and the semantic information extraction, then combines them into a single output that contains both the high-quality visual rendering and the extracted semantic data (such as tissue type classifications, lesion detections, and anatomical structures).
2Adaptability or versatility
If semantic processing is applied to extract semantic information from scan data, then clinical utility and tissue classification are improved, but processing time and computational complexity increase
Solution Approach 1:
The patent applies preliminary action by performing semantic information extraction during the volume rendering process itself, rather than as a separate post-processing step. The semantic processing is integrated into the rendering pipeline, where semantic information is extracted from the scan data or rendered images concurrently with or immediately after the cinematic rendering is generated. This preliminary integration reduces overall processing time by eliminating sequential execution of separate rendering and semantic extraction tasks.
3Measurement precision
If cinematic volume rendering is used instead of conventional ray tracing, then noise suppression and structure enhancement are improved, but semantic information extraction capability deteriorates
Solution Approach 1:
The patent applies feedback by using the cinematic volume rendering output as input for semantic information extraction. The high-quality rendered images, which contain enhanced structural information and suppressed noise, are fed back into the semantic processing pipeline. This feedback loop allows the semantic extraction process to benefit from the improved image quality, potentially extracting more accurate and reliable semantic information while maintaining the advantages of cinematic rendering.
Data Source
AI summary
The present embodiments relate to cinematic volume renderings and volumetric Monte-Carlo path tracing. The present embodiments include systems and methods for integrating semantic information into cinematic volume renderings. Scan data of a volume is captured by a scanner and transmitted to a server or workstation for rendering. The scan data is received by a server or workstation. The server or workstation extracts semantic information and/or applies semantic processing to the scan data. A cinematic volume rendering is generated from the scan data and the extracted semantic information.