Published Technical Disclosure Archive

Intelligent Endoscopic Imaging System for Enhanced Visualization and Guidance

Publication ID: 24-11857165_0010_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Intelligent Endoscopic Imaging System for Enhanced Visualization and Guidance,” Published Technical Disclosure No. 24-11857165_0010_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857165_0010_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. 11,857,165.

Summary of the Inventive Concept

The present inventive concept discloses a next-generation endoscopic imaging system that leverages machine learning, deep learning, and 3D modeling to provide unparalleled visualization and real-time guidance during medical procedures.

Background and Problem Solved

The original patent, 'Method for endoscopic imaging, endoscopic imaging system and software program product', introduced a method for capturing and displaying white light and special light images. However, it had limitations in terms of automation, real-time analysis, and advanced visualization capabilities. The present inventive concept addresses these limitations by introducing intelligent automation, advanced image analysis, and 3D modeling to provide a more comprehensive and efficient endoscopic imaging system.

Detailed Description of the Inventive Concept

The new endoscopic imaging system comprises a video endoscope with at least one CMOS image sensor, a light source configured to generate white light and at least one special light, and a controller. The controller is configured to detect structures having predefined characteristics and automatically adjust the special light illumination procedure to enhance visualization. Additionally, the system uses machine learning-based algorithms to predict and highlight areas of interest, and deep learning-based approaches to analyze image sequences and detect anomalies. The system can also generate 3D models of the examination surroundings and provide real-time guidance for optimal positioning of the video endoscope.

Novelty and Inventive Step

The new claims introduce novel features such as machine learning-based image analysis, deep learning-based anomaly detection, and 3D modeling for real-time guidance. These advancements provide a significant inventive step over the original patent, enabling more efficient and effective endoscopic imaging procedures.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, various deep learning architectures, or alternative 3D modeling techniques. Additionally, the system could be adapted for use in different medical specialties or for non-medical applications such as industrial inspection.

Potential Commercial Applications and Market

The intelligent endoscopic imaging system has significant commercial potential in the medical device industry, particularly in the fields of gastroenterology, urology, and general surgery. The system's advanced visualization and guidance capabilities could improve patient outcomes, reduce procedure times, and enhance the overall efficiency of medical procedures.

CPC Classifications

SectionClassGroup
A A61 A61B1/043
A A61 A61B1/000094
A A61 A61B1/044
A A61 A61B1/0638
A A61 A61B1/0655
G G06 G06F18/214
G G06 G06N3/08
G G06 G06V10/141
G G06 G06V10/143
H H04 H04N5/265
H H04 H04N23/74
G G06 G06V2201/032

Field of Art

Medical imaging technologies, specifically endoscopic imaging systems with advanced image processing and illumination techniques, involving interdisciplinary skills in medical device engineering, computer vision, machine learning, and image analysis

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with expertise in medical imaging technologies, proficient in CMOS sensor technologies, image processing algorithms, machine learning techniques, and endoscopic system design, typically holding an advanced engineering degree with 3-5 years of specialized experience

Obviousness Rationale

The published technical disclosure represents a predictable combination of known techniques in endoscopic imaging, where machine learning and deep learning approaches are applied to enhance existing image capture and analysis methodologies. A person having ordinary skill would recognize that integrating advanced computational techniques with established endoscopic imaging systems represents an incremental technological advancement rather than a non-obvious innovation. The core functional elements of light source, image sensor, and controller remain consistent with the source patent, with computational intelligence serving as a natural evolutionary extension of existing imaging technologies.

Obvious Combinations & Variations

Source Patent Element
Endoscopic imaging system with white light and special light illumination modes
PTD Variation
Adding machine learning-based algorithms to predict and highlight areas of interest during image capture
Obviousness Reasoning
Applying machine learning to image analysis is a known technique in medical imaging, representing a predictable optimization of existing image processing methods
Source Patent Element
Controller detecting structures with predefined characteristics
PTD Variation
Implementing deep learning approaches to analyze image sequences and detect anomalies
Obviousness Reasoning
Deep learning represents an evolutionary improvement in pattern recognition technologies, offering a straightforward enhancement to existing structure detection methodologies
Source Patent Element
Video endoscope with CMOS image sensor and light source
PTD Variation
Generating 3D models of examination surroundings and providing real-time positioning guidance
Obviousness Reasoning
3D reconstruction and guidance technologies are well-established in medical imaging, representing a logical extension of existing imaging capabilities
Source Patent Element
Synchronized alternating white light and special light illumination
PTD Variation
Automatically switching illumination modes using real-time computational analysis
Obviousness Reasoning
Automated mode switching is a predictable design optimization using computational intelligence, representing an incremental technological improvement
Source Patent Element
Endoscopic imaging system with multiple illumination modes
PTD Variation
Adapting system for different medical specialties and potential non-medical applications
Obviousness Reasoning
Cross-domain technology adaptation is a standard engineering practice, demonstrating the versatility of core technological concepts
35 U.S.C. § 103 Summary: Pursuant to 35 U.S.C. ยง 103, the variations disclosed in this published technical disclosure (PTD) would have been obvious to a person having ordinary skill in the art at the time of invention, with a reasonable expectation of success, when considered in light of US Patent 11857165. The incremental computational and algorithmic enhancements represent predictable variations that do not rise to the level of non-obvious innovation, thereby establishing this PTD as valid prior art for obviousness determinations.

Original Patent Information

Patent NumberUS 11,857,165
TitleMethod for endoscopic imaging, endoscopic imaging system and software program product
Assignee(s)OLYMPUS WINTER & IBE GMBH