ArticleIEEE transactions on medical imaging2017
Phase Vector Incompressible Registration Algorithm for Motion Estimation From Tagged Magnetic Resonance Images.
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 29 papers.
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Who cites it
29 citing papers in PubMed.
- DSHARP: Deep Incompressible Motion Estimation With Sinusoidal-Transformed Harmonic Phase for Tagged MRI.IEEE transactions on medical imaging · 2026Article
- Brightness-Invariant Tracking Estimation in Tagged MRI.Information processing in medical imaging : proceedings of the ... conference · 2026Article
- A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond.Medical image analysis · 2025Review
- Gross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model.Physics and imaging in radiation oncology · 2025Article
- Quantifying articulatory variations across phonological environments: An atlas-based approach using dynamic magnetic resonance imaging.The Journal of the Acoustical Society of America · 2024Article
- Tagged-to-Cine MRI Sequence Synthesis via Light Spatial-Temporal Transformer.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2024Article
- Investigating muscle coordination patterns with Granger causality analysis in protrusive motion from tagged and diffusion MRI.JASA express letters · 2024Article
- Speech Motion Anomaly Detection via Cross-Modal Translation of 4D Motion Fields from Tagged MRI.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Speech Audio Synthesis from Tagged MRI and Non-Negative Matrix Factorization via Plastic Transformer.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- Analysis of Tongue Muscle Strain During Speech From Multimodal Magnetic Resonance Imaging.Journal of speech, language, and hearing research : JSLHR · 2023Article
- Synthesizing Audio from Tongue Motion During Speech Using Tagged MRI Via Transformer.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury.Annals of biomedical engineering · 2021Review
- 3D amplified MRI (aMRI).Magnetic resonance in medicine · 2021Article
- A deep joint sparse non-negative matrix factorization framework for identifying the common and subject-specific functional units of tongue motion during speech.Medical image analysis · 2021Article
- DUAL-CYCLE CONSTRAINED BIJECTIVE VAE-GAN FOR TAGGED-TO-CINE MAGNETIC RESONANCE IMAGE SYNTHESIS.Proceedings. IEEE International Symposium on Biomedical Imaging · 2021Article
- Floor-of-the-Mouth Muscle Function Analysis Using Dynamic Magnetic Resonance Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2021Article
- In vivo estimates of axonal stretch and 3D brain deformation during mild head impact.Brain multiphysics · 2020Article
- Analysis of fiber strain in the human tongue during speech.Computer methods in biomechanics and biomedical engineering · 2020Article
- Identifying the Common and Subject-specific Functional Units of Speech Movements via a Joint Sparse Non-negative Matrix Factorization Framework.Proceedings of SPIE--the International Society for Optical Engineering · 2020Article
- Intermittently tagged real-time MRI reveals internal tongue motion during speech production.Magnetic resonance in medicine · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Tagged magnetic resonance imaging has been used for decades to observe and quantify motion and strain of deforming tissue. It is challenging to obtain 3-D motion estimates due to a tradeoff between image slice density and acquisition time. Typically, interpolation methods are used either to combine 2-D motion extracted from sparse slice acquisitions into 3-D motion or to construct a dense volume from sparse acquisitions before image registration methods are applied. This paper proposes a new phase-based 3-D motion estimation technique that first computes harmonic phase volumes from interpolated tagged slices and then matches them using an image registration framework. The approach uses several concepts from diffeomorphic image registration with a key novelty that defines a symmetric similarity metric on harmonic phase volumes from multiple orientations. The material property of harmonic phase solves the aperture problem of optical flow and intensity-based methods and is robust to tag fading. A harmonic magnitude volume is used in enforcing incompressibility in the tissue regions. The estimated motion fields are dense, incompressible, diffeomorphic, and inverse-consistent at a 3-D voxel level. The method was evaluated using simulated phantoms, human brain data in mild head accelerations, human tongue data during speech, and an open cardiac data set. The method shows comparable accuracy to three existing methods while demonstrating low computation time and robustness to tag fading and noise.
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