Beam Hardening Correction for CT Perfusion Measurements

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

This invention describes an improved method for reconstructing images in computed tomography (CT) perfusion scans. It uses a novel correction technique to address beam hardening artifacts by analyzing changes in image data over time, allowing for a clearer distinction between different tissues or components in the body and resulting in higher-quality enhanced images.

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

• Medical imaging in hospitals for better diagnosis of tissue perfusion (e.g., stroke analysis, tumor assessment)
• Research studies requiring precise CT imaging over time (dynamic studies)
• Radiology practices seeking improved image clarity for perfusion studies
• CT scanner manufacturers implementing advanced correction software in their devices

BenefitsContent extracted from patent full text and abstract with AI.

• Reduces artifacts in CT images caused by beam hardening
• Provides clearer distinction between different tissue types over time
• Improves the accuracy and diagnostic value of CT perfusion studies
• Enables higher-quality images without requiring hardware changes
• Facilitates better clinical decision-making due to enhanced imaging

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Patent Abstract

A method is disclosed for reconstructing image data of an examination subject from measured data, wherein a series of measured data sets has previously been acquired during a relative rotational movement between a radiation source of a computed tomography system and the examination subject and the measured data sets relate to the same section of the examination subject at succeeding instants in time. In at least one embodiment, first image data is reconstructed in each case from the measured data sets such that a series of first image data is available. A change variable indicating a change over time within the series of first image data is determined, and a distinction is made between different components of the examination subject in the first image data with the aid of the change variable. This distinction is used for beam hardening correction in an iterative algorithm for calculating enhanced image data.