Structured Learning for 3D Perivascular Spaces Segmentation Using Vascular Features
In this study, we propose a structured-learning-based segmentation framework to extract the perivascular spaces (PVSs) from high-resolution 7T MR images. Specifically, we integrate three types of vascular filter responses into a structured random forest for classifying each voxel into two categories.
Model-Based Estimation of Respiratory Parameters from Capnography, with Application to Diagnosing Obstructive Lung Disease
We develop a simple physiologically based mechanistic model of CO2 exhalation that closely accounts for the capnogram shape in normal subjects and in patients with obstructive lung disease. The model parameters – alveolar CO2 concentration, dead-space fraction, and exhalation time constant – are chosen to obtain a patient-specific fit to the recorded capnogram.
Electrical Impedance Tomography: Tissue Properties to Image Measures
Electrical Impedance Tomography (EIT) uses direct contact electrical stimulation and measurement at the body surface to image the electrical properties of internal tissues. EIT is useful when anatomical or physiological phenomena create contrasts in the tissue electrical properties, either through changes in the conductivity of tissue or the movement of conductively contrasting fluids or gasses.
Software Toolbox for Low-frequency Conductivity and Current Density Imaging using MRI
This MR-based conductivity imaging (MRCI) toolbox is available to download. It includes Matlab functions for image reconstructions in magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DTMREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI).
Electrical Properties Tomography Based on B1 Maps in MRI: Principles, Applications, and Challenges
We review the basic principle of electrical properties tomography (EPT), reconstruction methods, biomedical applications including tumor imaging, and existing challenges. As an important application of EPT, the estimation of specific absorption rate (SAR) and its current development will also be discussed.
Quantitative Susceptibility Mapping (QSM) Algorithms: Mathematical Rationale and Computational Implementations
This review paper focuses on algorithmic aspects of quantitative susceptibility mapping (QSM) that solves the magnetic field-to-magnetization inverse problem under conditions of noisy and incomplete field data acquired using MRI. The forward problem is presented as a partial differential equation, whose fundamental solution characterizes noise and model errors as streaking and shadow artifacts in susceptibility map reconstruction.