Surgical Space Image Registration Using Anatomical Semantics
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Solution Overview
Problem
The process of registering various visual representations of a surgical space generated by different imaging modalities is not straightforward, making it difficult to synthesize and provide intuitive visualizations for surgeons during procedures.
Innovation Solution
An image management system that accesses semantic information about anatomical objects to register datasets of visual representations, using scene segmentation, procedure phase, and force sensing data to align and update registrations based on reliable tissue features and instrument interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple imaging modalities are used to capture visual representations of the surgical site, then the quantity and variety of visual information is improved, but the complexity of registering and synthesizing these representations increases
Solution Approach 1:
The patent introduces an image management system as an intermediary that automatically performs registration of multiple visual representations. This intermediary system uses feature detection, landmark identification, and transformation algorithms to align images from different modalities (endoscopic, CT, MRI, ultrasound) without requiring manual intervention, thus resolving the contradiction between having multiple imaging sources and the complexity of registering them.
Solution Approach 2:
The patent replaces manual mechanical registration processes with automated computational methods. Instead of physically aligning images through manual manipulation, the system uses computer vision algorithms, feature point matching, and mathematical transformations to automatically register visual representations from multiple imaging modalities, significantly reducing the complexity of the registration process.
2Ease of operation
If manual registration methods are used to align visual representations, then the ease of operation is maintained, but the measurement precision and accuracy of registration deteriorates
Solution Approach 1:
The patent implements self-service automation where the image management system automatically performs registration tasks without requiring manual operation. The system detects features, identifies landmarks, computes transformations, and aligns images autonomously using algorithms that analyze image content and spatial relationships, thereby maintaining ease of operation while dramatically improving registration precision.
Solution Approach 2:
The patent employs feedback mechanisms where the system continuously evaluates registration accuracy by comparing registered features across multiple images. The automated system adjusts transformation parameters based on feedback from feature matching quality and landmark alignment, ensuring high precision registration while requiring minimal user intervention beyond initiating the process.
Data Source
AI summary
An exemplary image management system accesses semantic information regarding an anatomical object in a surgical space and registers, based at least in part on the semantic information regarding the anatomical object, a first dataset of a first visual representation of the surgical space with a second dataset of a second visual representation of the surgical space.