18186809. SYSTEMS AND METHODS FOR CLUTTER ARTIFACT REMOVAL simplified abstract (GE Precision Healthcare LLC)
Contents
SYSTEMS AND METHODS FOR CLUTTER ARTIFACT REMOVAL
Organization Name
Inventor(s)
[[:Category:Anders R. S�rnes of Oslo (NO)|Anders R. S�rnes of Oslo (NO)]][[Category:Anders R. S�rnes of Oslo (NO)]]
SYSTEMS AND METHODS FOR CLUTTER ARTIFACT REMOVAL - A simplified explanation of the abstract
This abstract first appeared for US patent application 18186809 titled 'SYSTEMS AND METHODS FOR CLUTTER ARTIFACT REMOVAL
Simplified Explanation: The patent application describes a method for reducing clutter artifacts in medical images using a data-driven model trained on image sequence pairs.
Key Features and Innovation:
- Method involves receiving a sequence of medical images with clutter artifacts and reducing them using a trained data-driven model.
- Model is trained on image sequence pairs with lower-clutter and higher-clutter images to effectively reduce artifacts.
- Display artifact-reduced version of medical images on a display device.
Potential Applications: This technology can be applied in medical imaging systems to improve the quality of images by reducing clutter artifacts, leading to more accurate diagnoses and treatment plans.
Problems Solved: This technology addresses the issue of clutter artifacts in medical images, which can hinder the interpretation of images by healthcare professionals and affect the accuracy of diagnoses.
Benefits:
- Improved image quality in medical imaging.
- Enhanced accuracy in diagnoses.
- Better visualization of medical conditions.
Commercial Applications: The technology can be utilized in medical imaging equipment and software to enhance the quality of medical images, potentially leading to increased efficiency and accuracy in healthcare settings.
Prior Art: Readers can explore prior art related to reducing clutter artifacts in medical images by researching existing image processing techniques and technologies used in medical imaging systems.
Frequently Updated Research: Stay informed about the latest advancements in image processing algorithms and data-driven models for medical image enhancement to further improve the quality of medical imaging.
Questions about Medical Image Artifact Reduction: 1. How does the trained data-driven model effectively reduce clutter artifacts in medical images? 2. What are the potential implications of using this technology in healthcare settings?
Original Abstract Submitted
The current disclosure provides systems and methods for reducing clutter artifacts in medical images. In one example, a method for an image processing system comprises receiving a sequence of medical images including an amount of clutter artifacts; reducing the amount of clutter artifacts present in the sequence of medical images using a trained data-driven model, the data-driven trained on image sequence pairs including a first, lower-clutter image sequence as a target image, and a second, higher-clutter image sequence as an input image, the higher-clutter image sequence generated by superimposing an artifact overlay on the lower-clutter image sequence, the lower-clutter image sequence generated by an imaging device during a medical exam of a subject; and displaying an artifact-reduced version of the sequence of medical images on a display device of the image processing system, the artifact-reduced version outputted by the data-driven model.
