Model-based elastography: a survey of approaches to the inverse elasticity problem

By Marvin M. Doyley. Physics in Medicine and Biology, 2012

333 citations recorded by the source corpus.

Elastography is emerging as an imaging modality that can distinguish normal versus diseased tissues via their biomechanical properties. This paper reviews current approaches to elastography in three areas—quasi-static, harmonic and transient—and describes inversion schemes for each elastographic imaging approach. Approaches include first-order approximation methods; direct and iterative inversion schemes for linear elastic; isotropic materials and advanced reconstruction methods for recovering parameters that characterize complex mechanical behavior. The paper's objective is to document efforts to develop elastography within the framework of solving an inverse problem, so that elastography may provide reliable estimates of shear modulus and other mechanical parameters. We discuss issues that must be addressed if model-based elastography is to become the prevailing approach to quasi-static, harmonic and transient elastography: (1) developing practical techniques to transform the ill-posed problem with a well-posed one; (2) devising better forward models to capture the complex mechanical behavior of soft tissues and (3) developing better test procedures to evaluate the performance of modulus elastograms.

Subfields: Biomedical Engineering, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/cd335920dba0c9dad04a071cd42309f107c2b489

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In Biomedical Engineering

1. Ming Dao
2. Subra Suresh
3. Enrui Zhang
4. G. Em Karniadakis
5. David D. Sampson
6. Kelsey M. Kennedy
7. B. Kennedy

In Radiology, Nuclear Medicine and Imaging

1. Enrui Zhang
2. Ming Dao
3. G. Em Karniadakis
4. David D. Sampson
5. Subra Suresh
6. Kelsey M. Kennedy
7. B. Kennedy

Citations in the corpus

• EFSUMB Guidelines and Recommendations on the Clinical Use of Ultrasound Elastography. Part 1: Basic Principles and Technology (2013, neutral): “Methods for calculating elasticity based on strain observations represent an example of solving “ the inverse problem ” in elasticity imaging [34].”
• A Review of Optical Coherence Elastography: Fundamentals, Techniques and Prospects (2014, background): “an assumed stress distribution (so-called inverse methods), are possible [86].”
• Analyses of internal structures and defects in materials using physics-informed neural networks (2022, methodology): “Modern experimental techniques have adopted dynamic external loading such as ultrasound (53) to acquire time-dependent measurements, through which we anticipate that the performance of our method will benefit from more information provided by measurements.”