Implicit 3D Rendering for Real-Time Views and Medical Privacy
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Solution Overview
Problem
Conventional image rendering methods require significant computing resources proportional to image resolution and fail to protect patient privacy due to embedded personal identifying information in medical images.
Innovation Solution
An image rendering system using a neural network-based implicit representation model, such as a neural radiance field, to compress and rotate three-dimensional images, generating two-dimensional images in real-time while protecting patient privacy through lossless compression and user-defined rotations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image rendering methods are used to store rendered images at high resolution, then image quality is improved, but computing resources and file size increase proportionally
Solution Approach 1:
The patent creates a compact implicit representation (neural radiance field) that serves as a compressed copy of the full 3D scene. Instead of storing complete high-resolution images or volumetric data, the system stores a condensed neural network model that can reconstruct images on-demand, dramatically reducing storage requirements while maintaining rendering quality.
Solution Approach 2:
The patent transforms the representation of 3D scenes from explicit voxel grids or mesh structures into implicit neural field representations. By changing the parameterization approach from discrete spatial coordinates to continuous neural network functions, the system achieves more efficient storage and faster rendering without sacrificing image quality.
2Measurement precision
If medical images are explicitly stored for rendering, then image quality is improved, but patient privacy is compromised due to embedded personal identifying information
Solution Approach 1:
The patent creates an implicit neural representation that captures the essential visual and structural information of medical images without preserving the original data format. This compressed representation maintains diagnostic quality while removing or obscuring embedded personal identifying information, as the neural field stores only the essential scene characteristics rather than raw pixel data containing metadata.
Solution Approach 2:
The patent extracts only the essential radiance and geometric information from medical images to construct the neural radiance field, leaving behind non-essential elements such as embedded metadata and personal identifying information. This selective extraction process retains diagnostic utility while eliminating privacy risks.
3Measurement precision
If high-resolution rendered images are generated, then image quality is improved, but rendering time and computational power increase
Solution Approach 1:
The patent performs preliminary work by training the neural radiance field model offline using a dataset of images from multiple viewpoints. This pre-training phase captures the essential 3D structure and appearance characteristics, enabling fast real-time rendering during the operational phase without requiring repeated heavy computations for each new view or resolution.
Solution Approach 2:
The patent implements a dynamic rendering approach where the neural radiance field can adaptively adjust its representation based on the desired output resolution and viewpoint. The system can render at different qualities by sampling the neural field at different densities, allowing real-time performance while maintaining the ability to produce high-resolution images when needed.
Data Source
AI summary
An image rendering system for rendering two-dimensional images in real-time. The image rendering system can receive an implicit representation model of a three-dimensional image. The image rendering system can construct, based on voxel coordinates, a three-dimensional image based on the implicit representation model. The image rendering system can rotate the three-dimensional image to an orientation in a computing space based on a user input. The image rendering system can generate a two-dimensional image based on the rotated three-dimensional image.