8 papers
Bayesian Estimation of Continuous Brain Connectivity with Log-Gaussian Cox Processes
Jaehoan Kim, William Consagra, Debdeep Pati +1
Continuous structural connectivity describes the connection between any two points of the cortical surface by an intensity function. Based on the endpoints of tractography streamli…
Prior-Guided Implicit Neural Representations for Single-Subject Diffusion MRI Super-Resolution
Abdulkader Ghandoura, Marsil Zakour, William Consagra +1
Resolving complex fiber geometries in brain white matter requires high-resolution diffusion MRI at the cost of long acquisition times. This leads many clinical protocols to opt for…
SIINR: Structurally Informed Implicit Neural Representations for super-resolution with uncertainty quantification of clinical quality diffusion MRI datasets
Tom Hendriks, William Consagra, Anna Vilanova +2
Diffusion Magnetic Resonance Imaging (dMRI) is a powerful tool for probing brain microstructure, but clinical acquisitions are often limited by low out-of-plane resolution, resulti…
Rapid Whole Brain Motion-robust Mesoscale In-vivo MR Imaging using Multi-scale Implicit Neural Representation
Jun Lyu, Lipeng Ning, William Consagra +4
High-resolution whole-brain in vivo MR imaging at mesoscale resolutions remains challenging due to long scan durations, motion artifacts, and limited signal-to-noise ratio (SNR). T…
Estimating Neural Orientation Distribution Fields on High Resolution Diffusion MRI Scans
Mohammed Munzer Dwedari, William Consagra, Philip Müller +3
The Orientation Distribution Function (ODF) characterizes key brain microstructural properties and plays an important role in understanding brain structural connectivity. Recent wo…
A Deep Learning Approach to Multi-Fiber Parameter Estimation and Uncertainty Quantification in Diffusion MRI
William Consagra, Lipeng Ning, Yogesh Rathi
Diffusion MRI (dMRI) is the primary imaging modality used to study brain microstructure in vivo. Reliable and computationally efficient parameter inference for common dMRI biophysi…
Neural Orientation Distribution Fields for Estimation and Uncertainty Quantification in Diffusion MRI
William Consagra, Lipeng Ning, Yogesh Rathi
Inferring brain connectivity and structure \textit{in-vivo} requires accurate estimation of the orientation distribution function (ODF), which encodes key local tissue properties.…
Optimized Diffusion Imaging for Brain Structural Connectome Analysis
William Consagra, Arun Venkataraman, Zhengwu Zhang
High angular resolution diffusion imaging (HARDI) is a type of diffusion magnetic resonance imaging (dMRI) that measures diffusion signals on a sphere in q-space. It has been widel…