ArticleIEEE transactions on medical imaging2017
Gradient-Based Optimization for Poroelastic and Viscoelastic MR Elastography.
Article in IEEE transactions on medical imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Article
- Clinical application of magnetic resonance elastography in pediatric neurological disorders.Pediatric radiology · 2023Review
- Mapping heterogenous anisotropic tissue mechanical properties with transverse isotropic nonlinear inversion MR elastography.Medical image analysis · 2022Article
- Evaluation of cerebral cortex viscoelastic property estimation with nonlinear inversion magnetic resonance elastography.Physics in medicine and biology · 2022Article
- MR elastography: Principles, guidelines, and terminology.Magnetic resonance in medicine · 2021Review
- Poroelastic Mechanical Properties of the Brain Tissue of Normal Pressure Hydrocephalus Patients During Lumbar Drain Treatment Using Intrinsic Actuation MR Elastography.Academic radiology · 2021Article
- A heterogenous, time harmonic, nearly incompressible transverse isotropic finite element brain simulation platform for MR elastography.Physics in medicine and biology · 2021Article
- Poroelasticity as a Model of Soft Tissue Structure: Hydraulic Permeability Reconstruction for Magnetic Resonance Elastography in Silico.Frontiers in physics · 2021Article
- Nonlinear Inversion MR Elastography With Low-Frequency Actuation.IEEE transactions on medical imaging · 2020Article
- Mechanical Identification of Materials and Structures with Optical Methods and Metaheuristic Optimization.Materials (Basel, Switzerland) · 2019Article
- Magnetic resonance elastography for examining developmental changes in the mechanical properties of the brain.Developmental cognitive neuroscience · 2018Review
- Stiffness reconstruction methods for MR elastography.NMR in biomedicine · 2018Review
- Analytical solution for converging elliptic shear wave in a bounded transverse isotropic viscoelastic material with nonhomogeneous outer boundary.The Journal of the Acoustical Society of America · 2018Article
- Article
- Gradient Based Elastic Property Reconstruction in Digital Image Correlation Elastography.Journal of medical physicsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
We describe an efficient gradient computation for solving inverse problems arising in magnetic resonance elastography (MRE). The algorithm can be considered as a generalized 'adjoint method' based on a Lagrangian formulation. One requirement for the classic adjoint method is assurance of the self-adjoint property of the stiffness matrix in the elasticity problem. In this paper, we show this property is no longer a necessary condition in our algorithm, but the computational performance can be as efficient as the classic method, which involves only two forward solutions and is independent of the number of parameters to be estimated. The algorithm is developed and implemented in material property reconstructions using poroelastic and viscoelastic modeling. Various gradient- and Hessian-based optimization techniques have been tested on simulation, phantom and in vivo brain data. The numerical results show the feasibility and the efficiency of the proposed scheme for gradient calculation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.