Published Technical Disclosure Archive

Next-Generation Hollow Organ Imaging System

Publication ID: 24-11857145_0005_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Hollow Organ Imaging System,” Published Technical Disclosure No. 24-11857145_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857145_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. 11,857,145.

Summary of the Inventive Concept

A system for generating multi-contrast agent image data of a hollow organ, enabling personalized diagnosis and treatment through advanced material separation and machine learning-based analysis.

Background and Problem Solved

The original patent provided a method for providing image data of a hollow organ, but it had limitations in terms of contrast agent usage and image data analysis. The new inventive concept addresses these limitations by introducing a multi-spectral CT scanner and advanced material separation algorithms, enabling more accurate and personalized diagnoses.

Detailed Description of the Inventive Concept

The next-generation hollow organ imaging system comprises a multi-spectral CT scanner, a processing unit, and a machine learning module. The CT scanner acquires spectrally resolved CT data of the hollow organ, which is then separated into multiple material images corresponding to specific contrast agents. The machine learning module identifies regions of interest in the image data and separates them into different material classes based on the absorption spectra of multiple contrast agents. This enables the generation of personalized image data and 3D representations of the hollow organ, allowing for more accurate diagnoses and treatments.

Novelty and Inventive Step

The new claims introduce the concept of multi-spectral CT scanning, advanced material separation algorithms, and machine learning-based analysis, which are not present in the original patent. These features enable a more accurate and personalized diagnosis of hollow organ diseases, making the new inventive concept novel and non-obvious compared to the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different types of CT scanners, such as photon-counting CT scanners, or the integration of additional imaging modalities, such as MRI or ultrasound. Variations of the material separation algorithms and machine learning models could also be explored to further improve the accuracy and personalization of the image data.

Potential Commercial Applications and Market

The next-generation hollow organ imaging system has significant commercial potential in the medical imaging industry, particularly in the diagnosis and treatment of gastrointestinal diseases. The system's ability to provide personalized image data and accurate diagnoses could lead to improved patient outcomes and reduced healthcare costs. The target market includes hospitals, clinics, and medical research institutions.

CPC Classifications

SectionClassGroup
A A61 A61B6/481
A A61 A61B6/032
A A61 A61B6/4241
A A61 A61B6/469
A A61 A61B6/50
A A61 A61B6/5205
A A61 A61M5/007

Field of Art

Medical Imaging and Diagnostic Radiology, specifically computed tomography (CT) scanning techniques for hollow organ visualization, requiring expertise in medical imaging technologies, contrast agent applications, and advanced image processing algorithms

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with advanced degrees in medical imaging, biomedical engineering, or radiological sciences, possessing comprehensive knowledge of CT scanning technologies, spectral imaging techniques, and image processing methodologies

Obviousness Rationale

A person having ordinary skill in the art would recognize that the PTD's machine learning-enhanced multi-spectral CT imaging represents a predictable technological progression from the source patent's foundational hollow organ imaging method. The disclosed variations leverage known computational techniques and imaging technologies to extend the original patent's core imaging approach. These modifications represent incremental improvements that would be apparent to a skilled practitioner seeking to enhance diagnostic capabilities through advanced image processing and material separation techniques.

Obvious Combinations & Variations

Source Patent Element
Spectrally resolved computed tomography data acquisition for hollow organ imaging
PTD Variation
Integration of machine learning modules for automated region of interest identification and material classification
Obviousness Reasoning
Applying machine learning to spectral imaging is a known technique for enhancing diagnostic image analysis, representing a predictable technological evolution with expected improvements in diagnostic accuracy
Source Patent Element
First and second contrast agent application for lumen visualization
PTD Variation
Multi-spectral CT scanning with advanced material separation algorithms to generate personalized image representations
Obviousness Reasoning
Expanding contrast agent techniques to generate more detailed material-specific imaging is a logical extension of existing medical imaging methodologies, representing a finite and predictable solution to improving diagnostic capabilities
Source Patent Element
Computed tomography data generation for hollow organ assessment
PTD Variation
3D representation generation with machine learning-based abnormality detection
Obviousness Reasoning
Transforming 2D imaging data into 3D representations with computational analysis is a well-established technique in medical imaging, representing an obvious technological progression with expected diagnostic benefits
Source Patent Element
Photon counting computed tomography data acquisition
PTD Variation
Patient-specific absorption spectrum analysis for personalized imaging
Obviousness Reasoning
Customizing imaging techniques based on individual patient characteristics is a known approach in precision medicine, representing a predictable application of existing imaging technologies
Source Patent Element
Contrast agent filling of organ lumen
PTD Variation
Modular contrast agent delivery system with coordinated multi-agent application
Obviousness Reasoning
Developing more sophisticated contrast agent delivery mechanisms is an obvious engineering solution to improve imaging precision, representing a finite set of potential technological improvements
35 U.S.C. § 103 Summary: Pursuant to 35 U.S.C. ยง 103, the variations disclosed in this Published Technical Disclosure would have been obvious to a person having ordinary skill in the art at the time of invention, with reasonable expectation of success, when considering the teachings of US Patent 11857145. The incremental technological advancements represent predictable extensions of the source patent's core imaging methodology, utilizing known computational and medical imaging techniques to enhance diagnostic capabilities through machine learning, multi-spectral analysis, and personalized imaging approaches.

Original Patent Information

Patent NumberUS 11,857,145
TitleMethod for providing image data of a hollow organ
Assignee(s)Siemens Healthcare Limited