Medical Image Rendering with Uncertainty-Scaled Optical Properties
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Solution Overview
Problem
Modern AI-based segmentation tools in medical imaging face challenges in achieving high-performance, high-quality three-dimensional volume rendering without latency issues, particularly in real-time applications, often resulting in distracting visual artifacts at segmentation boundaries that impede spatial understanding.
Innovation Solution
A method for volume and surface rendering of medical imaging data sets based on optical properties per sampling points, using an uncertainty indicator to scale randomization of sampling points, which includes determining optical properties per point and rendering based on these properties, thereby avoiding disruptive changes and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional smoothing operations (distance transform, interpolation) are applied to binary segmentation masks, then rendering quality is improved, but processing time and latency increase
Solution Approach 1:
The patent replaces conventional mechanical smoothing operations (distance transform, interpolation algorithms) with a physics-based radiative transfer approach. Instead of applying computational smoothing filters to binary masks, the system uses optical property assignment and light transport simulation to achieve smooth rendering effects, substituting mechanical computational processes with a different physical modeling paradigm that avoids the latency of traditional pre-processing pipelines
Solution Approach 2:
The patent changes the fundamental parameters of the rendering process by assigning optical properties (absorption coefficient μa, scattering coefficient μs, anisotropy g) to segmentation regions instead of applying spatial smoothing to the mask itself. This parameter transformation allows the rendering engine to produce smooth visual results through optical property variation rather than mask modification, eliminating the need for time-consuming pre-processing steps
2Productivity
If fast rendering algorithms are used, then processing speed is improved, but visual artifacts at segmentation boundaries appear
Solution Approach 1:
The patent applies local quality by assigning different optical properties to different spatial regions defined by segmentation masks. Each segmentation region receives tailored optical parameters (absorption, scattering, anisotropy) that are optimized for that specific tissue type or anatomical structure. This localized parameter assignment maintains sharp segmentation boundaries while allowing smooth transitions through optical property variation, avoiding the visual artifacts that plague fast rendering algorithms while preserving rendering speed
Solution Approach 2:
The patent introduces optical properties as an intermediary layer between the binary segmentation mask and the final rendered image. Instead of directly rendering the discrete mask data, the system first assigns continuous optical properties to each segmented region, which then serve as intermediaries that smooth the transition between discrete segmentation classes during the rendering process, eliminating boundary artifacts while maintaining fast rendering performance
Data Source
AI summary
A technique for volume rendering, and/or surface rendering, of a medical imaging data set based on optical properties per sampling points is provided. An uncertainty indicator per voxel, and/or per surface element, in relation to a segmentation mask of, and/or an anatomical structure comprised in, a medical imaging data set is received. A randomization of one or more sampling points is scaled based on the received uncertainty indicator, and at least one optical property per sampling point is determined. A volume based on the voxels, and/or a surface based on the surface elements is rendered. The rendering is based on the determined at least one optical property per sampling point.