Advanced Catheter Navigation System with AI-Driven Visualization

Publication ID: 24-11857276_0005_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Advanced Catheter Navigation System with AI-Driven Visualization,” Published Technical Disclosure No. 24-11857276_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857276_0005_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,276.

Summary of the Inventive Concept

A next-generation catheter navigation system that leverages artificial intelligence, machine learning, and advanced visualization techniques to provide real-time guidance and enhance navigation accuracy in minimally invasive procedures.

Background and Problem Solved

The original patent disclosed a system for displaying an alignment CT, which, while effective, has limitations in terms of accuracy and real-time feedback. The new inventive concept addresses these limitations by introducing AI-driven visualization and machine learning-based segmentation to provide more accurate and personalized navigation.

Detailed Description of the Inventive Concept

The advanced catheter navigation system comprises a neural network trained on CT image data to predict optimal catheter trajectories, a visualization module to display the predicted trajectories in real-time, and a hybrid rendering engine utilizing both Maximum Intensity Projection (MIP) and Volume Rendering (VR) techniques to provide an unobstructed view of the target region. The system also incorporates real-time catheter tracking using augmented reality (AR) visualization to project the catheter's position and trajectory onto the patient's body. Furthermore, the system generates personalized 3D models of patient airways from CT image data using a generative adversarial network (GAN) to refine the 3D model and improve navigation accuracy.

Novelty and Inventive Step

The new claims introduce novel AI-driven visualization and machine learning-based segmentation techniques that significantly improve navigation accuracy and provide real-time feedback. The use of a neural network to predict optimal catheter trajectories, the hybrid rendering engine, and the incorporation of AR visualization are all non-obvious and innovative steps beyond the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of other machine learning algorithms, such as deep learning or reinforcement learning, to improve navigation accuracy. Additionally, the system could be adapted for use in other minimally invasive procedures, such as cardiovascular or neurosurgical interventions.

Potential Commercial Applications and Market

The advanced catheter navigation system has significant commercial potential in the medical device industry, particularly in the fields of pulmonology, cardiology, and neurosurgery. The system's ability to provide real-time guidance and enhance navigation accuracy could lead to improved patient outcomes, reduced procedure times, and increased adoption of minimally invasive procedures.

CPC Classifications

SectionClassGroup
A A61 A61B34/20
A A61 A61B34/25
A A61 A61B90/37
G G06 G06T15/00
A A61 A61B1/018
A A61 A61B1/2676
A A61 A61B10/02
A A61 A61B2017/00809
A A61 A61B2034/107
A A61 A61B2034/2051
A A61 A61B2034/2055
A A61 A61B2034/2061
A A61 A61B2034/2065
A A61 A61B2034/2068
A A61 A61B2034/2072
A A61 A61B2090/367
A A61 A61B2090/3925
A A61 A61M2025/0166

Field of Art

Medical imaging and interventional navigation systems, specifically focusing on CT-guided catheter navigation and visualization techniques in minimally invasive medical procedures. Requires expertise in medical imaging, computer vision, 3D rendering, and medical device navigation technologies

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical imaging specialist with advanced degrees in bioengineering, computer science, or medical technology, possessing expertise in medical image processing, machine learning, 3D visualization techniques, and interventional medical device design

Obviousness Rationale

A PHOSITA would recognize that the advanced AI-driven visualization and navigation techniques represent predictable extensions of existing medical imaging technologies. The proposed machine learning and augmented reality approaches are logical progressions of known medical imaging and navigation methodologies, utilizing standard computational techniques to enhance existing catheter navigation systems. The incremental improvements in trajectory prediction, rendering techniques, and real-time visualization would be considered obvious refinements to a skilled practitioner in the field.

Obvious Combinations & Variations

Source Patent Element
3D rendering of patient's airways using transfer functions and voxel density
PTD Variation
Hybrid rendering engine utilizing Maximum Intensity Projection (MIP) and Volume Rendering (VR) techniques
Obviousness Reasoning
Combining different rendering techniques is a known approach in medical imaging to improve visualization, representing a predictable design optimization that would be obvious to a PHOSITA seeking enhanced diagnostic clarity
Source Patent Element
Catheter navigation system with computing device for generating 3D views
PTD Variation
Neural network trained on CT image data to predict optimal catheter trajectories
Obviousness Reasoning
Application of machine learning to medical imaging navigation is a well-established technique, representing an obvious technological progression for improving precision and automated guidance
Source Patent Element
System for identifying target locations within patient airways
PTD Variation
Generative adversarial network (GAN) to refine 3D models and improve navigation accuracy
Obviousness Reasoning
Using advanced machine learning techniques to enhance medical imaging models is a predictable evolution in the field, representing an obvious optimization approach for a skilled practitioner
Source Patent Element
Computing device for generating views of patient's internal structures
PTD Variation
Augmented reality (AR) visualization to project catheter position and trajectory onto patient's body
Obviousness Reasoning
Integrating AR visualization is a logical extension of existing medical imaging technologies, representing an obvious enhancement to provide more intuitive navigation guidance
Source Patent Element
Three-dimensional rendering of patient airways
PTD Variation
Personalized 3D models generated using machine learning segmentation techniques
Obviousness Reasoning
Customizing 3D medical models through advanced computational techniques is a predictable approach for improving diagnostic and navigational precision
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857276 and the disclosed technical variations, a person having ordinary skill in the art would find the proposed AI-driven catheter navigation and visualization techniques to be obvious extensions of existing medical imaging technologies. The incremental improvements in machine learning, rendering techniques, and navigation guidance represent predictable technological progressions that would be readily conceived by a skilled practitioner in the field of medical imaging and interventional navigation systems.

Original Patent Information

Patent NumberUS 11,857,276
TitleSystem and method for displaying an alignment CT
Assignee(s)Covidien LP