Neural Network Visualization for 3D Catheter Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Atrial fibrillation ablation procedures face challenges in accurately navigating an ablation catheter to the pulmonary veins due to difficulties in understanding the orientation and position of the catheter relative to the 3D anatomy of the heart, particularly when using intracardiac echocardiography (ICE), requiring extensive experience.
Innovation Solution
A system that uses neural networks to provide visualization within a 3D model by receiving a query image, extracting neural network encodings, querying a synthetic image repository for matching images, and displaying an estimated region of interest within the 3D model, aiding medical professionals with precise visual guides.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If ICE is used for navigation, then real-time imaging is obtained, but understanding catheter orientation and position relative to 3D anatomy becomes difficult
Solution Approach 1:
The patent introduces an intermediary system consisting of a 3D anatomical model and image matching algorithms that mediate between the raw ICE images and the operator's understanding. The query image is matched against a repository of synthetic images derived from 3D models, providing an intermediate representation that bridges the gap between 2D imaging and 3D spatial comprehension.
Solution Approach 2:
The patent transforms the problem from 2D image interpretation to 3D spatial understanding by matching ICE images with 3D model-based synthetic images. This dimensionality change allows operators to visualize catheter position in the context of 3D cardiac anatomy rather than interpreting isolated 2D frames.
2Reliability
If traditional navigation methods are used, then procedure experience can be accumulated, but procedure time and complexity increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing cardiac anatomy data into 3D models and generating a repository of synthetic images before the actual ablation procedure. This preparation work is done in advance, allowing during-procedure image matching to be performed quickly without requiring extensive real-time processing or operator experience accumulation.
Solution Approach 2:
The patent creates synthetic copies of the patient's cardiac anatomy from 3D models and stores them in a repository. These synthetic images serve as reference copies that can be rapidly compared with actual ICE images during the procedure, eliminating the need for operators to mentally reconstruct 3D anatomy from multiple 2D images.
3Ease of operation
If manual image interpretation is used, then operator judgment is applied, but precision in localizing regions of interest decreases
Solution Approach 1:
The patent implements a feedback mechanism where the system automatically matches query images with synthetic images from the repository, provides feedback on the best matches, and highlights corresponding regions in the 3D model. This automated feedback loop enhances operator judgment by providing objective, algorithm-based localization suggestions that can be quickly verified or adjusted.
Data Source
AI summary
Apparatus for visualization within a three-dimensional (3D) model and methods used therein are described, wherein the apparatus includes a processor and a memory communicatively connected to the processor, wherein the memory includes instructions configuring the processor to receive a query image, extract neural network encodings from the received query image, query a synthetic image repository for at least a matching synthetic image, and display an estimated region of interest within the 3D model, wherein the synthetic image repository includes a plurality of synthetic images and their extracted neural network encodings, each synthetic image therein corresponds to a region of interest in the 3D model, and querying the synthetic image repository includes comparing the extracted neural network encodings between the query image and synthetic images.