Geometric Localisation in Medical Imaging

Publication: EP4467081A1
Published: 2024-11-27
Family Size: 2
Granted: No

Patent Abstract

A geometric ultrasound localisation microscopy method is provided according to one embodiment for localising microbubbles. The proposed method uses a novel geometry framework for microbubble localisation through ellipse or ellipsoid intersections to overcome limitations inherent to beamforming. This approach provides a finer distinction between overlapping and clustered spots, improving localisation precision, reliability, and computation efficiency. The present invention thus challenges the conventional wisdom that beamforming is necessary for ULM and proposes a novel beamformer-free approach that according to one example relies on time difference of arrival information between echoes for microbubble localisation.

Simple SummaryContent extracted from patent full text and abstract with AI.

This invention introduces a novel geometric localisation method for medical imaging, specifically for localising microbubbles used in ultrasound localisation microscopy (ULM). Instead of the traditional beamforming approach, the method uses a geometry-based system relying on the intersection of ellipses (or ellipsoids) constructed from echo time-of-arrival data from multiple sensors. This enables more precise, reliable, and efficient localisation of microbubbles or small particles within the body, without needing expensive or computationally heavy beamforming algorithms.

Use CasesContent extracted from patent full text and abstract with AI.

  • High-resolution imaging of vascular structures in organs (e.g., liver, kidney, brain) to assist in disease diagnosis.
  • Differentiation and diagnosis of tumor types, such as in kidney or breast cancer detection.
  • Functional imaging of neurovascular activity (e.g., brain activity mapping).
  • Tracking and monitoring microbubbles or particles in contrast-enhanced ultrasound exams.
  • Potential application to localisation tasks in other imaging modalities like MRI or CT, where precise spatial mapping of particles is needed.
  • Guidance for minimally invasive surgeries and targeted therapy using precise microbubble detection.

BenefitsContent extracted from patent full text and abstract with AI.

  • Increases localisation precision and reliability for medical imaging, surpassing beamforming limitations.
  • Reduces computational burden and memory requirements by removing the need for beamforming.
  • Enhances detection of overlapping and clustered microbubbles or particles, improving image clarity.
  • Broadens application scope by not being limited to specific transducer geometries or arrangements.
  • Improves real-time imaging capabilities due to faster and more efficient processing.
  • Facilitates easier implementation in portable or resource-constrained imaging devices.

Technical Classifications (CPCs)

Main Classifications

Health, Food & Consumer Tech

Sub Classifications

Medical & Vet Science

CPC Codes

A61B8/4477A61B8/481A61B8/5223

Inventors & Applicants

Inventors

Christopher Hahne

Raphael Sznitman

Applicant(s)

Univ Bern

Key Information

Publication No.

EP4467081A1

Family ID

86497634

Publication Date

2024-11-27

Application No.

EP23174686A

Application Date

2023-05-22

Priority Date

2023-05-22

Granted

No

Possible Cooperation

For further information please contact the transfer office.