On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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5 results for “Dynamic-MRI”

Characterization of surface motion patterns in highly deformable soft tissue organs from dynamic MRI: An application to assess 4D bladder motioncs.CV

Study characterizes bladder motion using dynamic MRI and statistical analysis.

problem Limited volume coverage in dynamic MRI sequences hinders 3D shape reconstruction.

method 3D dense velocity measurements, LDDMM framework, statistical characterization, mean curvature changes, surface deformation analysis.

result Stable shape descriptor for characterizing bladder surface dynamics.

Dynamic MRI Soft tissue organs Bladder motion Surface deformation LDDMM

2020-10-05abs ↗pdf ↗

Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recoveryeess.IV

Paper proposes a new method for MRI data recovery using bi-linear modeling.

problem Recovering high-fidelity MRI data from dynamic sequences.

method Bi-linear modeling framework for manifold learning and sparse approximation.

result The method improves MRI data recovery over existing techniques.

MRI Dynamic-MRI Manifold Learning Sparse Approximation Bi-linear Modeling

2018-12-27abs ↗pdf ↗

Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completionstat.ML

Streaming tensor factorization is a powerful tool for processing high-volume and multi-way temporal data in Internet networks, recommender systems and image/video data analysis. Existing streaming tensor factorization algorithms rely on least-squares data fitting and they do not possess a mechanism for tensor rank dete…

2018-09-06abs ↗pdf ↗

Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Casecs.LG

Paper develops a novel kernel-based method for MRI data recovery.

problem Reconstructing dynamic MRI data on manifolds.

method Kernel bi-linear modeling in reproducing kernel Hilbert spaces.

result Validated on synthetic dMRI data, the method outperforms state-of-the-art approaches.

MRI Reconstruction Kernel Methods Dynamic Data Reproducing Kernel Hilbert Spaces

2020-02-27abs ↗pdf ↗

Structured Low-Rank Algorithms: Theory, MR Applications, and Links to Machine Learningcs.CV

Survey of structured low-rank algorithms for MR signal recovery.

problem Recovering multidimensional signals from few non-uniform measurements.

method Structured low-rank matrix completion formulation.

result Performance guarantees and fast algorithms for large-scale MR problems.

structured low-rank matrix completion MRI applications compressed sensing fast algorithms

2019-10-27abs ↗pdf ↗