Enhanced Functional OCT Data Processing

Publication ID: 24-11857257_0006_PTD
Published: November 07, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Functional OCT Data Processing,” Published Technical Disclosure No. 24-11857257_0006_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857257_0006_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. 11,857,257.

Summary of the Inventive Concept

An improved system and method for processing functional OCT image data, utilizing machine learning, GPU acceleration, adaptive window size selection, and parallel or distributed computing to enhance the accuracy and efficiency of retina response analysis.

Background and Problem Solved

The original patent disclosed an apparatus for processing functional OCT image data, but it had limitations in terms of processing time, accuracy, and adaptability. The new inventive concept addresses these limitations by introducing novel enhancements to the correlation calculator module, enabling faster, more accurate, and more efficient retina response analysis.

Detailed Description of the Inventive Concept

The enhanced system comprises a receiver module, a correlation calculator module, and a response generator module. The correlation calculator module utilizes machine learning algorithms trained on a dataset of known retina responses, GPU acceleration to reduce processing time by at least 50%, adaptive window size selection to optimize correlation calculation, or parallel or distributed computing architectures to further accelerate processing. These enhancements enable the generation of more accurate indications of retina responses to light stimuli, facilitating improved diagnosis and treatment of retinal diseases.

Novelty and Inventive Step

The new claims introduce novel enhancements to the correlation calculator module, including the use of machine learning algorithms, GPU acceleration, adaptive window size selection, and parallel or distributed computing architectures. These enhancements provide a significant improvement over the original patent, enabling faster, more accurate, and more efficient retina response analysis.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, varying GPU acceleration techniques, or alternative parallel or distributed computing architectures. Additionally, the system could be adapted for use with different types of OCT imaging devices or in combination with other diagnostic tools.

Potential Commercial Applications and Market

The enhanced system and method for processing functional OCT image data have significant commercial potential in the medical diagnostics industry, particularly in the diagnosis and treatment of retinal diseases such as age-related macular degeneration. The target market includes ophthalmology clinics, hospitals, and research institutions.

CPC Classifications

SectionClassGroup
A A61 A61B3/102
A A61 A61B3/0008
A A61 A61B3/0025
G G06 G06T7/0012
G G06 G06T7/11
G G06 G06T2207/30041

Field of Art

Medical imaging and signal processing, specifically optical coherence tomography (OCT) data analysis, involving advanced computational techniques for medical diagnostic imaging

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with expertise in medical imaging, signal processing, machine learning, and high-performance computing, typically holding a PhD or equivalent professional experience in biomedical engineering, computer science, or related fields

Obviousness Rationale

A person having ordinary skill would recognize that the proposed enhancements to functional OCT data processing represent predictable improvements using standard computational techniques. The machine learning, GPU acceleration, and parallel processing approaches are well-established methods for enhancing computational performance and analysis accuracy in medical imaging domains. These variations represent straightforward extensions of the source patent's core methodology of correlating OCT image data with stimulus indicators.

Obvious Combinations & Variations

Source Patent Element
Correlation calculator module for processing OCT image sequences and stimulus indicators
PTD Variation
Incorporating machine learning algorithms to train and optimize correlation calculations
Obviousness Reasoning
Machine learning techniques are a known method for improving signal processing and pattern recognition in medical imaging, representing a predictable application of existing computational techniques
Source Patent Element
Sequential processing of B-scan image data
PTD Variation
Implementing GPU acceleration to reduce processing time by at least 50%
Obviousness Reasoning
GPU parallel processing is a standard technique for computational acceleration in signal and image processing, offering a predictable performance improvement with well-understood implementation strategies
Source Patent Element
Fixed window correlation calculation method
PTD Variation
Adaptive window size selection algorithm for dynamic correlation processing
Obviousness Reasoning
Adaptive algorithmic approaches are a recognized optimization technique in signal processing, representing a design choice that would be obvious to a skilled practitioner seeking improved computational efficiency
Source Patent Element
Single-machine OCT data processing approach
PTD Variation
Distributed computing framework to reduce processing time by at least 75%
Obviousness Reasoning
Distributed and parallel computing architectures are standard techniques for handling computationally intensive medical imaging tasks, representing a predictable extension of existing processing methodologies
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857257 and the disclosed technical variations, a person having ordinary skill in the art would find the proposed enhancements to functional OCT data processing obvious and predictable. The combination of machine learning, GPU acceleration, adaptive processing, and distributed computing represents a straightforward application of known computational techniques to the existing OCT data processing methodology, thereby rendering potential derivative claims obvious and unpatentable.

Original Patent Information

Patent NumberUS 11,857,257
TitleFunctional oct data processing
Assignee(s)OPTOS PLC