Reference-Based Integral MR-EPT: Simulation and Experiment Studies at 9.4T MRI
Magnetic resonance electrical properties tomography (MR-EPT) is an emerging technology which plays an important role in specific absorption rate monitoring. The current integral-equation (IE) based MR-EPT methods utilize simulated incident radio-frequency (RF) fields, which are inaccurate and lead to reconstruction errors. In this work, the incident field approximation (IFA) is first demonstrated. IFA utilizes a reference subject and RF field mapping techniques to map the incident field, hence the loading effect of the RF coil can be involved in the IE-based MR-EPT. This method may push the IE-based MR-EPT into practical utilization at UHF-MRI systems.
Automatic Recognition of fMRI-derived Functional Networks using 3D Convolutional Neural Networks
Automatic and accurate classification and recognition of fMRI-derived functional brain networks are very important for subsequent steps of functional brain analysis. We design a deep 3D CNN framework for automatic and accurate classification and recognition of numbers of functional brain networks. Our work provides a new deep learning approach for modeling functional connectomes based on fMRI data.
Volume 62, Issue 4, Page:1120 - 1131 Holistic Atlases of Functional Networks and Interactions Reveal Reciprocal Organizational Architecture of Cortical Function
For decades, it has been largely unknown how and to what extent multiple functional networks spatially overlap/interact with each other and jointly realize the total cortical function…