MCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction

• Published in: IEEE transactions on medical imaging Vol. 42; no. 12; pp. 3512 - 3523
• Main Authors: Guo, Xueqi, Zhou, Bo, Chen, Xiongchao, Chen, Ming-Kai, Liu, Chi, Dvornek, Nicha C.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Benchmarks; Deep learning; Dynamics; Error correction; Fitting; Image enhancement; Image reconstruction; Image warping; Inter-frame motion correction; Kinetic theory; Kinetics; Misalignment; Motion estimation; Motion simulation; Neural networks; Optimization; parametric imaging; Patlak loss optimization; Positron emission; Positron emission tomography; whole-body dynamic PET

In whole-body dynamic positron emission tomography (PET), inter-frame subject motion causes spatial misalignment and affects parametric imaging. Many of the current deep learning inter-frame motion correction techniques focus solely on the anatomy-based registration problem, neglecting the tracer ki...