Unoccluded 3D Anatomy Visualization via Depth Buffer Clipping
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Solution Overview
Problem
Current medical imaging systems face challenges in visualizing deep-seated anatomy in 3D without occlusion, as traditional methods require user interaction and can lead to perceptual distortions due to global opacity modulation and lack of depth continuity.
Innovation Solution
A method and system for 3D un-occluded visualization that involves generating a volumetric data set, performing semantic segmentation to filter out the focus from context, estimating depth buffers for focus and context, clipping eye and light rays based on these buffers, and generating a rendered 3D image using a volumetric clipping surface, preserving depth cues and minimizing distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If global opacity modulation is used to remove occluding context, then visibility of focus is improved, but depth continuity between focus and context is lost leading to perceptual distortions
Solution Approach 1:
The patent segments the volumetric data into focus regions and context regions using semantic segmentation. By dividing the volume into distinct segments with separate depth buffers, the system can selectively render focus regions without occlusion while preserving the spatial relationships and depth continuity with surrounding context structures.
Solution Approach 2:
The patent applies local quality by creating separate depth buffers for focus and context regions, allowing different rendering treatments for different parts of the volume. The focus region receives special handling with occlusion removal while context regions maintain their original depth information, enabling localized optimization without global distortion.
2Loss of information
If multiple 2D slices are viewed to assess deep-seated anatomy, then complete visual inspection is achieved, but diagnostic time and fatigue increase
Solution Approach 1:
The patent transitions from 2D slice-based visualization to 3D volume rendering with selective occlusion removal. By rendering anatomy in three dimensions and selectively removing occluding structures, the system provides complete visual inspection of deep-seated anatomy in a single integrated view rather than requiring navigation through multiple 2D slices.
Solution Approach 2:
The patent extracts and removes occluding context structures from the visualization using semantic segmentation and selective rendering. By taking out the interfering elements (occluding bones and musculature), the system allows direct visualization of deep-seated anatomy without requiring the radiologist to mentally reconstruct information from multiple slices.
3Loss of information
If semantic segmentation is used to selectively remove occluding context, then visibility of focus is improved, but depth continuity is not preserved leading to perceptual distortions
Solution Approach 1:
The patent uses semantic segmentation to divide volumetric data into focus and context regions, then applies separate depth buffer estimation for each segment. This segmentation approach allows selective rendering of focus regions while maintaining accurate depth relationships with context, preventing perceptual distortions.
Solution Approach 2:
The patent introduces depth buffers as an intermediary mechanism between semantic segmentation and final rendering. The depth buffers store depth information for both focus and context regions, acting as a mediator that preserves spatial relationships and depth continuity even when context structures are selectively removed for improved focus visibility.
Data Source
AI summary
Unoccluded visualization of Anatomy in Volumetric Data. Embodiments disclosed herein relate to medical imaging systems, and more particularly to medical visualization systems, which can be used for visualizing anatomy. Embodiments herein disclose methods and systems for enabling unoccluded visualization of anatomy of interest in volumetric data. Embodiments herein disclose 3D visualization techniques for visualization of deep seated anatomy with no user interactions, while preserving depth continuity with surrounding(s) and with minimal distortion for improved clinical assessment.