Published Technical Disclosure Archive

AI-Enhanced Standalone Endoscopic Objective Image Analysis System

Publication ID: 24-11857151_0005_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “AI-Enhanced Standalone Endoscopic Objective Image Analysis System,” Published Technical Disclosure No. 24-11857151_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857151_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. 11,857,151.

Summary of the Inventive Concept

A next-generation standalone endoscopic objective image analysis system that leverages AI-driven image processing, real-time anomaly detection, and cloud-based deep learning models to provide comprehensive, 3D-reconstructed images of target areas and objective performance metrics.

Background and Problem Solved

The original patent, 'Systems and methods for standalone endoscopic objective image analysis', addressed the need for evaluating the performance of an endoscope's objective. However, this approach has limitations, including the need for manual evaluation and the lack of real-time feedback. The new inventive concept addresses these limitations by introducing AI-driven image processing, real-time anomaly detection, and cloud-based deep learning models to provide a more efficient, accurate, and comprehensive evaluation of endoscope objectives.

Detailed Description of the Inventive Concept

The AI-enhanced standalone endoscopic objective image analysis system comprises a modular, AI-driven image processing module that receives and analyzes a plurality of intermediate images captured from a standalone objective. The module generates a comprehensive, 3D-reconstructed image of the target area and provides objective performance metrics. The system also integrates a real-time, machine learning-based anomaly detection algorithm, enabling real-time alerts and notifications for objective-related issues. The system can be cloud-based, allowing for remote access and collaboration. The AI-driven image processing module utilizes a deep learning model trained on a large dataset of endoscope objectives to generate the comprehensive, 3D-reconstructed image and objective performance metrics.

Novelty and Inventive Step

The new inventive concept introduces AI-driven image processing, real-time anomaly detection, and cloud-based deep learning models, which are not present in the original patent. These features enable a more efficient, accurate, and comprehensive evaluation of endoscope objectives, providing a significant improvement over the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include integrating the AI-driven image processing module with other medical devices, such as microscopes or surgical robots, to provide real-time image analysis and feedback. Another variation could be the use of edge computing or fog computing to enable real-time processing and analysis of images at the point of care.

Potential Commercial Applications and Market

The AI-enhanced standalone endoscopic objective image analysis system has significant commercial potential in the medical device industry, particularly in the areas of endoscopy, microscopy, and surgical robotics. The system could be marketed as a standalone device or integrated into existing medical devices, providing a competitive advantage to manufacturers and improving patient outcomes.

CPC Classifications

SectionClassGroup
A A61 A61B1/00009
A A61 A61B1/04
G G06 G06T5/003
G G06 G06T5/006
G G06 G06T7/0012
H H04 H04N23/67
G G06 G06T5/005
G G06 G06T7/174
G G06 G06T2207/10068
G G06 G06T2207/20221
G G06 G06T2207/30168
H H04 H04N23/6845
H H04 H04N23/951

Field of Art

Medical imaging technologies, specifically endoscopic image analysis systems, involving optical engineering, image processing, and machine learning techniques for medical diagnostic equipment

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with expertise in biomedical engineering, computer vision, optical systems design, and AI-driven image analysis, holding advanced degrees in engineering or computer science with practical experience in medical imaging technologies

Obviousness Rationale

A PHOSITA would recognize that integrating AI-driven image processing and machine learning techniques into the existing endoscopic objective image analysis framework represents a predictable technological evolution. The source patent's foundational image capture and analysis methodology provides a clear technical foundation for enhancing the system with advanced computational techniques. The proposed AI and cloud-based extensions represent natural progressions in medical imaging technology that would be obvious to implement given the rapid advancement of machine learning and distributed computing platforms.

Obvious Combinations & Variations

Source Patent Element
Image capture system configured to capture multiple intermediate images of a formed image from an endoscope objective
PTD Variation
AI-driven image processing module generating 3D-reconstructed images from multiple intermediate images using deep learning models
Obviousness Reasoning
Applying machine learning techniques to image reconstruction is a known approach in medical imaging, representing a predictable application of existing computational methods to improve image analysis capabilities
Source Patent Element
Image processing system configured to identify in-focus portions of intermediate images
PTD Variation
Real-time machine learning-based anomaly detection algorithm for identifying objective performance issues
Obviousness Reasoning
Extending image analysis capabilities to include automated anomaly detection is a logical extension of existing image processing techniques, utilizing well-established machine learning classification approaches
Source Patent Element
Standalone objective evaluation system with movable camera along optical axis
PTD Variation
Cloud-based AI platform for remote image processing and performance metric generation
Obviousness Reasoning
Transitioning from local to cloud-based computational analysis represents a standard technological progression in distributed computing, offering predictable improvements in computational flexibility and scalability
Source Patent Element
Objective image quality evaluation system
PTD Variation
Integration with additional medical devices like microscopes and surgical robots for comprehensive image analysis
Obviousness Reasoning
Cross-platform technology integration is a common design approach in medical imaging, representing a straightforward extension of existing technological frameworks
Source Patent Element
Image capture and processing methodology for endoscopic objectives
PTD Variation
Edge computing implementation for real-time image processing at point of care
Obviousness Reasoning
Implementing distributed computing architectures is a predictable technological evolution in medical imaging systems, representing a known technique for improving computational efficiency
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857151 and the disclosed technological variations, a person having ordinary skill in the art would find the proposed AI-enhanced endoscopic objective image analysis system obvious and anticipated, as the claimed innovations represent predictable technological extensions of existing image capture and processing methodologies in medical imaging technologies.

Original Patent Information

Patent NumberUS 11,857,151
TitleSystems and methods for standalone endoscopic objective image analysis
Assignee(s)STERIS Instrument Management Services, Inc.