How Medical Scanners Track Surgical Tools in Real-Time
This patent describes a method for medical imaging devices to accurately show the real-time 3D position of surgical tools and implants inside a patient during an operation, using a combination of initial 3D scans and live 2D X-ray images.
Original patent title: “Method and device for operating a medical imaging device for the positionally correct representation of non-anatomical structures during an imaging examination”
This patent describes a method for medical imaging devices to accurately show the real-time 3D position of surgical tools and implants inside a patient during an operation, using a combination of initial 3D scans and live 2D X-ray images. Granted to Ziehm Imaging in 2025 with 17 claims, and it is expected to expire in 2042.
Coverage
What does this patent actually cover?
The patent details a method for medical imaging systems to precisely track non-anatomical structures, like surgical instruments, inside a patient during a procedure. It starts with an initial 3D scan (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1) to create a detailed anatomical model. Then, it continuously takes new 2D X-ray images (Claim 1) and uses machine learning to identify both the patient's anatomy and the surgical tools within these images (Claim 10). The system reconstructs a 3D view of the tools from these 2D images, removing visual clutter using machine learning (Claim 1). It then aligns this live 3D view of the tools with the initial detailed anatomical model, creating a "navigation volume" (Claim 1) that shows where the tools are in relation to the patient's body. For example, a surgeon could see the exact 3D path of a guide wire (Claim 14) as it moves through a blood vessel, overlaid on a pre-operative CT scan.
The gap
What does this patent NOT cover?
- Does not cover systems that only use a single initial 3D image without continuous 2D updates to track structures.
- Does not cover tracking non-anatomical structures without first extracting an anatomical model from an initial 3D image.
- Does not cover methods that calculate the non-anatomical 3D image without using machine learning to remove artifacts from partial 3D reconstructions.
- Does not cover systems that track non-anatomical structures without registering the live anatomical 3D image with the initial 3D image to determine a coordinate transformation.
- Does not cover methods that do not combine the anatomical model and the non-anatomical 3D image into a "navigation volume" using the determined coordinate transformation.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The noveltynoveltyThe requirement that an invention be different from anything publicly known before its priority date.Read more → lies in combining initial high-resolution 3D anatomical data with real-time, lower-resolution 2D images to dynamically track non-anatomical objects in 3D. It specifically uses machine learning to clean up the 3D reconstructions of these objects and accurately register them within the patient's overall anatomy.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Image-guided neurosurgery systems
Cardiac catheterization labs
Orthopedic surgery navigation
Interventional radiology suites
C-arm X-ray systems with navigation capabilities
Why it matters
The bigger picture
This technology is important for image-guided surgery and interventional procedures, where precision is critical. By providing real-time, positionally correct 3D views of instruments like catheters or guide wires (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 14) within a patient's anatomy, it can help surgeons navigate complex areas, reduce risks, and improve patient outcomes. It enables more accurate placement of implants and devices.
Filed
July 29, 2022
Granted
July 15, 2025
Market context
Who's building on this
Companies in this space
Ziehm Imaging GmbH, the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is a major player in mobile C-arm X-ray systems, which are central to this technology. Other companies like Medtronic, Siemens Healthineers, Philips Healthcare, and Brainlab are also active in image-guided surgery and navigation, constantly integrating advanced imaging and AI for better surgical outcomes.
Market impact
This patent addresses a critical need for improved real-time guidance in minimally invasive procedures. Its application of machine learning for artifact removal and precise registration could lead to more accurate and safer surgeries, potentially reducing procedure times and complications. It strengthens the capabilities of image-guided surgery platforms, making them more reliable for tracking dynamic elements like guide wires and catheters.
Claim 1 — Plain English
What this patent covers
The patent details a method for medical imaging systems to precisely track non-anatomical structures, like surgical instruments, inside a patient during a procedure. It starts with an initial 3D scan (Claim 1) to create a detailed anatomical model. Then, it continuously takes new 2D X-ray images (Claim 1) and uses machine learning to identify both the patient's anatomy and the surgical tools within these images (Claim 10). The system reconstructs a 3D view of the tools from these 2D images, removing visual clutter using machine learning (Claim 1). It then aligns this live 3D view of the tools with the initial detailed anatomical model, creating a "navigation volume" (Claim 1) that shows where the tools are in relation to the patient's body. For example, a surgeon could see the exact 3D path of a guide wire (Claim 14) as it moves through a blood vessel, overlaid on a pre-operative CT scan.
The clever bit
The novelty lies in combining initial high-resolution 3D anatomical data with real-time, lower-resolution 2D images to dynamically track non-anatomical objects in 3D. It specifically uses machine learning to clean up the 3D reconstructions of these objects and accurately register them within the patient's overall anatomy.
What it does not cover
- Does not cover systems that only use a single initial 3D image without continuous 2D updates to track structures.
- Does not cover tracking non-anatomical structures without first extracting an anatomical model from an initial 3D image.
- Does not cover methods that calculate the non-anatomical 3D image without using machine learning to remove artifacts from partial 3D reconstructions.
- Does not cover systems that track non-anatomical structures without registering the live anatomical 3D image with the initial 3D image to determine a coordinate transformation.
- Does not cover methods that do not combine the anatomical model and the non-anatomical 3D image into a "navigation volume" using the determined coordinate transformation.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
Patent enters public domain
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
11/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$43K – $137K
Midpoint $86K · 15.9 yr remaining · industry ×2.2
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
17 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
König, T., Hörndler, K., Vöth, T., KNAUP, M., & Kachelriess, M. (2025). How Medical Scanners Track Surgical Tools in Real-Time (U.S. Patent No. 12,357,189). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12357189/method-and-device-for-operating-a-medical-imaging-device-for-the-positionally-co
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Medical Scanners Track Surgical Tools in Real-Time cover?
This patent describes a method for medical imaging devices to accurately show the real-time 3D position of surgical tools and implants inside a patient during an operation, using a combination of initial 3D scans and live 2D X-ray images.
Who owns patent US 12357189?
Ziehm Imaging owns this patent, granted in 2025.
When does this patent expire?
This patent is expected to expire on July 29, 2042, when the invention enters the public domain.
What problem does this patent solve?
This technology is important for image-guided surgery and interventional procedures, where precision is critical. By providing real-time, positionally correct 3D views of instruments like catheters or guide wires (Claim 14) within a patient's anatomy, it can help surgeons navigate complex areas, reduce risks, and improve patient outcomes. It enables more accurate placement of implants and devices.
What does this patent NOT cover?
Does not cover systems that only use a single initial 3D image without continuous 2D updates to track structures.
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