Adaptive Multispectral Imaging Systems for Enhanced Surgical Visualization

Publication ID: 24-11857154_0005_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Adaptive Multispectral Imaging Systems for Enhanced Surgical Visualization,” Published Technical Disclosure No. 24-11857154_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857154_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. 11,857,154.

Summary of the Inventive Concept

A next-generation surgical imaging system that leverages machine learning, neural networks, and real-time feedback to optimize illumination settings for enhanced visual acuity during medical procedures.

Background and Problem Solved

The original patent's closed-loop surgical imaging optimization system, while innovative, has limitations in its ability to adapt to real-time changes in tissue characteristics and visual acuity requirements. The new inventive concept addresses these limitations by incorporating advanced machine learning algorithms and neural networks to adaptively adjust illumination wavelengths in real-time.

Detailed Description of the Inventive Concept

The new system comprises a neural network-based image processing module that analyzes multispectral image data and adjusts illumination settings in real-time based on tissue characteristics and visual acuity requirements. The system also includes a feedback loop to refine illumination settings during the medical procedure. Additionally, the system can be integrated with wearable devices, cloud-based platforms, and predictive modeling tools to provide real-time analytics and recommendations for optimal illumination settings.

Novelty and Inventive Step

The new claims introduce a paradigm shift in surgical imaging optimization by incorporating machine learning and neural networks to adaptively adjust illumination wavelengths in real-time. This is a significant departure from the original patent's closed-loop approach, which relied on pre-defined settings and annotations.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, such as deep learning or transfer learning, or the integration of additional sensors, such as optical coherence tomography (OCT) or ultrasound. Variations could also include the use of different types of wearable devices or cloud-based platforms.

Potential Commercial Applications and Market

The inventive concept has significant commercial potential in the medical device industry, particularly in the areas of minimally invasive surgery, endoscopy, and laparoscopy. The system's ability to enhance visual acuity and reduce complications during medical procedures could lead to improved patient outcomes and reduced healthcare costs.

CPC Classifications

SectionClassGroup
A A61 A61B1/000095
A A61 A61B1/00009
A A61 A61B1/00013
A A61 A61B1/04
A A61 A61B1/045
A A61 A61B1/0638
A A61 A61B1/0655
A A61 A61B1/07
A A61 A61B34/25
A A61 A61B90/37
A A61 A61B2090/306
A A61 A61B2090/3614
A A61 A61B2090/371

Field of Art

Medical imaging systems, specifically surgical visualization technologies involving endoscopic and laparoscopic imaging with advanced processing techniques

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical imaging specialist with expertise in computer vision, image processing, machine learning, and surgical visualization technologies, holding advanced degrees in bioengineering or medical technology with 3-5 years of practical experience

Obviousness Rationale

A person having ordinary skill would recognize that the PTD's neural network-based image optimization represents a predictable technological evolution from the source patent's closed-loop imaging system. The fundamental concept of adaptive image processing remains consistent, with the primary difference being the incorporation of machine learning techniques to dynamically adjust illumination parameters. These modifications represent an incremental technological advancement that would be obvious to a skilled practitioner familiar with emerging medical imaging technologies.

Obvious Combinations & Variations

Source Patent Element
Closed-loop image processing system with user annotations and real-time image comparison
PTD Variation
Neural network-based image processing module with adaptive illumination wavelength adjustment
Obviousness Reasoning
Applying machine learning to existing closed-loop imaging systems represents a known technique for enhancing automated image processing, with predictable results of improved visual acuity
Source Patent Element
Surgical camera generating multispectral image streams
PTD Variation
Machine learning algorithms analyzing multispectral image data to identify optimal illumination wavelengths
Obviousness Reasoning
Extending image analysis capabilities through computational techniques is a standard approach in medical imaging, representing an obvious design optimization
Source Patent Element
Medical image display system with user interface for storing and retrieving images
PTD Variation
Cloud-based platform with centralized multispectral image database and collaborative interface
Obviousness Reasoning
Transitioning from local to cloud-based storage and analysis is a predictable technological progression in medical imaging systems
Source Patent Element
Processing modules for exchanging data between surgical camera and display systems
PTD Variation
Wearable device with see-through display overlaying multispectral image data
Obviousness Reasoning
Integrating display technologies with surgical imaging represents a logical extension of existing medical visualization techniques
35 U.S.C. § 103 Summary: Pursuant to 35 U.S.C. ยง 103, the variations disclosed in this publication would be considered obvious to a person having ordinary skill in medical imaging technologies, as exemplified by the teachings of US Patent 11857154. The incremental advancements in machine learning, neural network processing, and adaptive imaging techniques represent predictable technological progressions that do not rise to the level of non-obvious innovation.

Original Patent Information

Patent NumberUS 11,857,154
TitleSystems and methods for closed-loop surgical imaging optimization