Anatomy Object Identification Interface for Dynamic Navigation
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Solution Overview
Problem
Existing medical imaging systems fail to accurately depict the spatial relationship between a medical instrument and a target during an intraoperative phase due to anatomical changes and deviations from preoperative images, leading to inaccurate navigation.
Innovation Solution
A method and system that registers updated intraoperative image data with sensor data to facilitate real-time navigation by generating a volumetric view and receiving user inputs to determine the object's position within the anatomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If preoperative images are used to navigate to the target during intraoperative phase, then navigation can be planned in advance, but the spatial relationship becomes inaccurate due to anatomical changes
Solution Approach 1:
The system transitions from static preoperative images to dynamic intraoperative images that are continuously updated during the procedure. The imaging system captures real-time images of the anatomy and the medical instrument, and the processor dynamically updates the display to reflect current spatial relationships, accommodating anatomical changes as they occur during the procedure.
Solution Approach 2:
The system incorporates real-time feedback by continuously capturing intraoperative images and comparing them with the current state of the anatomy and instrument. The processor uses this feedback to update the spatial relationship information displayed to the user, ensuring that navigation guidance remains accurate despite anatomical changes or instrument repositioning during the procedure.
2Ease of operation
If preoperative images are used for navigation, then the workflow is simplified, but navigation accuracy deteriorates due to anatomical changes
Solution Approach 1:
The system maintains ease of operation by providing a unified interface that handles both preoperative planning and intraoperative navigation through the same workflow. The processor automatically updates the spatial relationship information based on real-time images, eliminating the need for manual re-planning while maintaining high accuracy despite anatomical changes.
Solution Approach 2:
The system performs self-updating of spatial relationship information automatically. The imaging system continuously captures images of the anatomy and instrument, and the processor autonomously processes these images to update the display without requiring manual intervention or re-planning, thus maintaining both simplicity and accuracy throughout the procedure.
3Measurement precision
If real-time imaging is implemented to update spatial relationships, then navigation accuracy is improved, but system complexity increases
Solution Approach 1:
The imaging system is designed to perform multiple functions: capturing preoperative images for planning, capturing intraoperative images for real-time updates, and processing both types of images through a unified workflow. This multi-functionality reduces the need for separate systems and streamlines the overall complexity while maintaining high accuracy.
Solution Approach 2:
The processor automatically handles the complex tasks of image capture, processing, and spatial relationship calculation without requiring manual intervention. The system self-updates the display based on real-time images, automating what would otherwise be complex manual re-planning procedures and reducing the operational complexity burden on the user.
Data Source
AI summary
This disclosure provides methods, devices, and systems for planning and performing medical procedures. The present implementations more specifically relate to techniques for identifying an object (such as a medical instrument or a nodule) in an anatomy based on image data representing a three-dimensional (3D) model of the anatomy. In some aspects, a controller for a medical system may filter the image data based on known properties of the object (such as an expected image intensity distribution associated with the object) and generate a volumetric view of the anatomy based on the filtered image data so that the object is highlighted in the volumetric view. The controller further displays a graphical user interface (GUI) that includes the volumetric view of the anatomy and determines a pose of the object within the anatomy based on one or more user inputs received via the GUI.