Integrative Cardiac Strain Analysis Systems with Advanced Technologies

Publication ID: 24-11857288_0003_PTD
Published: November 07, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Integrative Cardiac Strain Analysis Systems with Advanced Technologies,” Published Technical Disclosure No. 24-11857288_0003_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857288_0003_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. 11,857,288.

Summary of the Inventive Concept

The inventive concept integrates deep learning-based phase unwrapping for dense MRI with distinct technologies such as AI, IoT, blockchain, and new materials to create a more powerful system for cardiac strain analysis, offering enhanced accuracy, security, and real-time monitoring capabilities.

Background and Problem Solved

The original patent addressed the challenge of myocardial strain imaging, which is sensitive and prognostic for heart disease assessment. However, the original patent's method had limitations in terms of data security, real-time monitoring, and integration with other technologies. The new inventive concept addresses these limitations by integrating the patented deep learning-based phase unwrapping with advanced technologies, enabling a more comprehensive and powerful system for cardiac strain analysis.

Detailed Description of the Inventive Concept

The inventive concept comprises a deep learning-based phase unwrapping module integrated with one or more of the following advanced technologies: AI-powered analytics platforms, IoT-enabled sensor networks, blockchain-based data encryption and secure sharing mechanisms, and new material-based wearable devices. The system enables real-time monitoring of cardiac health, secure data sharing, and enhanced strain analysis capabilities. The AI-powered analytics platform can analyze data from various sources, including wearable devices and IoT-enabled sensors, to provide a more comprehensive understanding of cardiac health. The blockchain-based data encryption and secure sharing mechanism ensures the secure storage and transmission of sensitive medical data. The new material-based wearable devices enable real-time monitoring of cardiac health, providing early detection of potential heart problems.

Novelty and Inventive Step

The new claims introduce a synergistic combination of distinct technologies, which provides a novel and non-obvious solution for cardiac strain analysis. The integration of deep learning-based phase unwrapping with AI, IoT, blockchain, and new materials enables a more powerful and comprehensive system that addresses the limitations of the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept may include varying the type of AI algorithm used, the specific IoT-enabled sensors employed, the blockchain architecture utilized, or the new materials incorporated into the wearable devices. Additionally, the system could be adapted for use in other medical imaging modalities or applications beyond cardiac strain analysis.

Potential Commercial Applications and Market

The inventive concept has significant commercial potential in the medical imaging and healthcare industries, particularly in the areas of cardiac disease diagnosis and treatment. The system's ability to provide enhanced accuracy, security, and real-time monitoring capabilities makes it an attractive solution for hospitals, research institutions, and medical device manufacturers.

Field of Art

Medical imaging, specifically cardiac magnetic resonance imaging (MRI) with deep learning techniques for strain analysis and image processing

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical imaging specialist with expertise in MRI technologies, deep learning neural networks, signal processing, and medical data analysis, holding advanced degrees in bioengineering, computer science, or medical imaging

Obviousness Rationale

A PHOSITA would recognize that integrating additional technologies like IoT, blockchain, and AI with the existing deep learning phase unwrapping method for cardiac MRI represents a predictable combination of known techniques in medical imaging and digital health. The source patent's foundation of using U-Net CNN for phase unwrapping provides a clear technological basis for extending the system's capabilities through complementary technologies. These variations represent standard engineering approaches to enhancing medical imaging systems by incorporating contemporary digital technologies.

Obvious Combinations & Variations

Source Patent Element
U-Net structured CNN for phase unwrapping in DENSE MRI
PTD Variation
Integrating AI-powered analytics platform for enhanced strain analysis
Obviousness Reasoning
Extending machine learning techniques to provide additional data processing is a known and predictable approach in medical imaging, representing a straightforward application of existing deep learning methodologies
Source Patent Element
Displacement encoded MRI data processing
PTD Variation
Adding IoT-enabled sensor networks for real-time cardiac health monitoring
Obviousness Reasoning
Incorporating continuous monitoring technologies is a standard method for expanding medical diagnostic capabilities, with predictable results in improving patient care and data collection
Source Patent Element
Cardiac strain analysis using deep learning techniques
PTD Variation
Implementing blockchain-based data encryption for secure medical data sharing
Obviousness Reasoning
Applying blockchain security mechanisms to medical imaging data represents a logical extension of existing data protection strategies in digital healthcare systems
Source Patent Element
Phase unwrapping method for MRI image processing
PTD Variation
Developing new material-based wearable devices for continuous cardiac monitoring
Obviousness Reasoning
Adapting medical imaging technologies to wearable form factors is a predictable innovation in medical device engineering, representing a finite set of design solutions
35 U.S.C. § 103 Summary: Based on US Patent 11857288's teachings of deep learning-based phase unwrapping for cardiac MRI, the present disclosure demonstrates that a person of ordinary skill in the art would find the integration of IoT, blockchain, AI, and advanced materials into cardiac strain analysis systems an obvious technological extension, rendering potential claims in this domain anticipated and non-patentable under 35 U.S.C. ยง 103.

Original Patent Information

Patent NumberUS 11,857,288
TitleSystems and methods for phase unwrapping for dense MRI using deep learning
Assignee(s)University of Virginia Patent Foundation