Medical Image Overlay Alignment via Differentiable Rendering
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Solution Overview
Problem
Conventional differentiable rendering techniques are not applied to heterogeneous volume data from medical scanners, leading to inefficiencies in photorealistic overlay rendering due to high computational complexity and time, especially for medical images.
Innovation Solution
A method involving differentiable rendering of intermediate representations of medical and reference images, using gradient descent to optimize rendering parameters for alignment and overlay, enabling photorealistic overlays of heterogeneous medical data efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If physically-based Monte Carlo light transport is used to simulate light paths with multiple scattering events, then photorealistic rendering quality is improved, but computational time and complexity increase significantly
Solution Approach 1:
The patent pre-computes and stores light transport properties (phase functions, absorption coefficients, scattering properties) in lookup tables before the actual rendering process. This preliminary action allows the Monte Carlo simulation to use pre-prepared data rather than computing everything from scratch, significantly reducing real-time computational time while maintaining photorealistic quality
Solution Approach 2:
The system performs preliminary segmentation and extraction of anatomical structures from medical images before rendering. This pre-processing creates ready-to-use geometric models and material properties that accelerate the subsequent Monte Carlo light transport simulation, enabling real-time performance
2Productivity
If conventional volume visualization methods with ray casting are used, then computational speed is improved, but photorealistic quality with global illumination is lost
Solution Approach 1:
The patent segments the volume data into distinct anatomical structures (organs, tissues, bones) with different optical properties. This segmentation allows the system to apply optimized rendering strategies to each structure type, combining fast ray casting for simple regions with photorealistic Monte Carlo simulation for complex scattering regions, thus achieving both speed and quality
Solution Approach 2:
The system applies different rendering quality levels to different regions of the image based on local requirements. Critical anatomical structures with complex light scattering (e.g., translucent tissues) receive full photorealistic Monte Carlo treatment, while other regions use faster conventional methods, optimizing the balance between overall quality and computational speed
3Adaptability or versatility
If differentiable rendering is applied to heterogeneous volume data, then gradient-based optimization capability is improved, but computational memory requirements increase
Solution Approach 1:
The patent pre-computes and stores derivative information and intermediate representation data in compressed formats before optimization begins. This preliminary preparation reduces the memory footprint during the actual gradient-based optimization process, allowing differentiable rendering to be applied to large heterogeneous volume datasets without excessive memory requirements
Data Source
AI summary
An overlay of an aligned medical image obtained from a medical scanner is rendered with a reference image. The reference image has a reference structure of a body. An intermediate representation of the reference structure is determined. The medical image has structures corresponding to the reference structures, and an intermediate representation of the structures in the medical image is determined. A rendering parameter is optimized by comparing the intermediate representations of the medical image and of the reference image. The medical image is aligned and overlayed with the reference image based on the optimized rendering parameter, and the aligned and overlayed image is rendered.