System and method of perceptive quantitative mapping of physical properties

US11782112B2 · kind B2 · utility

Assignee

• Cornell University · IT

Inventors

• Yi Wang · New York, US
• Zhe Liu · Changchun, CN
• Jinwei Zhang · Ningbo City, CN
• Qihao Zhang · New York, US
• Junghun Cho · New York, US
• Pascal Spincemaille · New York, US

Key dates

• Filing date: May 28, 2020
• Grant date: Oct 10, 2023
• Expiry date: May 28, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/20084
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Exemplary methods for quantitative mapping of physical properties, systems and computer-accessible medium can be provided to generate images of tissue magnetic susceptibility, transport parameters and oxygen consumption from magnetic resonance imaging data using the Bayesian inference approach, which minimizes a data fidelity term under a constraint of a structure prior knowledge. The data fidelity term is constructed directly from the magnetic resonance imaging data. The structure prior knowledge can be characterized from known anatomic images using image feature extraction operation or artificial neural network. Thus, according to the exemplary embodiment, system, method and computer-accessible medium can be provided for determining physical properties associated with at least one structure.