Time-Resolved Phase Contrast MR Imaging with Velocity Encoding

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This patent presents a method and technology for time-resolved phase-contrast magnetic resonance imaging (MR imaging), which uses speed encoding to capture dynamic data. The system detects MR signals in multiple time frames with several receivers, identifies stationary and moving image points, applies a locally variable mask, and reconstructs high-quality images using an iterative process with temporal regularization.

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

• Non-invasive cardiovascular imaging to assess blood flow over time.
• Diagnosis of vascular diseases like stenosis or aneurysms.
• Monitoring heart valve function and abnormalities.
• Imaging cerebrospinal fluid dynamics in neurology.
• Research into organ or tissue motion during different physiological processes.

BenefitsContent extracted from patent full text and abstract with AI.

• Enables more precise and dynamic visualization of moving tissues and fluids such as blood.
• Improves diagnostic accuracy by distinguishing stationary from moving structures.
• Reduces imaging artifacts and enhances image quality through advanced reconstruction techniques.
• Supports better monitoring and assessment of treatment effects in cardiovascular and neurological diseases.
• Offers a non-invasive method for detailed functional imaging.

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Patent Abstract

In a method and apparatus for time-resolved phase-contrast magnetic resonance (MR) imaging with speed encoding, MR signals are detected with multiple receivers in each of numerous time segments in order to acquire raw data in each of the time segments, in each case for numerous MR images with different speed encodings. Stationary image points and/or non-stationary image points are identified, dependent on the detected MR signals. A mask is defined, dependent on the identified stationary image points and/or the non-stationary image points, wherein the mask is locally variable. The numerous MR images for the numerous time segments are reconstructed from the acquired raw data, wherein the reconstruction occurs in an iterative process and with a temporal regularization, which is dependent on the mask.