Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues.The quality of reconstruction results in elastography is highly sensitive to the noise induce...Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues.The quality of reconstruction results in elastography is highly sensitive to the noise induced by imaging measurements and processing.To address this issue,we propose a deep learning(DL)model based on conditional Generative Adversarial Networks(cGANs)to improve the quality of nonhomogeneous shear modulus reconstruction.To train this model,we generated a synthetic displacement field with finite element simulation under known nonhomogeneous shear modulus distribution.Both the simulated and experimental displacement fields are used to validate the proposed method.The reconstructed results demonstrate that the DL model with synthetic training data is able to improve the quality of the reconstruction compared with the well-established optimization method.Moreover,we emphasize that our DL model is only trained on synthetic data.This might provide a way to alleviate the challenge of obtaining clinical or experimental data in elastography.Overall,this work addresses several fatal issues in applying the DL technique into elastography,and the proposed method has shown great potential in improving the accuracy of the disease diagnosis in clinical medicine.展开更多
In the stratified atmosphere in which the moment nondivergent approximation was applied,introducing the nonlinear term because of the nonhomogcneous spatial distribution of density and assuming the solution to be of t...In the stratified atmosphere in which the moment nondivergent approximation was applied,introducing the nonlinear term because of the nonhomogcneous spatial distribution of density and assuming the solution to be of the form of progressive wave,we obtain a two-order nonlinear system.By means of this system,all results which were derived by Liu et al.(1984)were obtained.Moreover,it can be proved that there existed periodic solution in the nonlinear systems when there existed periodic solution in the one-order approxima- tion system,and some mathematic problems arising from series expansion were avoided.In this paper,a series of approximate solutions of nonlinear system is also discussed.展开更多
基金National Natural Science Foundation of China (12002075)National Key Research and Development Project (2021YFB3300601)Natural Science Foundation of Liaoning Province in China (2021-MS-128).
文摘Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues.The quality of reconstruction results in elastography is highly sensitive to the noise induced by imaging measurements and processing.To address this issue,we propose a deep learning(DL)model based on conditional Generative Adversarial Networks(cGANs)to improve the quality of nonhomogeneous shear modulus reconstruction.To train this model,we generated a synthetic displacement field with finite element simulation under known nonhomogeneous shear modulus distribution.Both the simulated and experimental displacement fields are used to validate the proposed method.The reconstructed results demonstrate that the DL model with synthetic training data is able to improve the quality of the reconstruction compared with the well-established optimization method.Moreover,we emphasize that our DL model is only trained on synthetic data.This might provide a way to alleviate the challenge of obtaining clinical or experimental data in elastography.Overall,this work addresses several fatal issues in applying the DL technique into elastography,and the proposed method has shown great potential in improving the accuracy of the disease diagnosis in clinical medicine.
文摘In the stratified atmosphere in which the moment nondivergent approximation was applied,introducing the nonlinear term because of the nonhomogcneous spatial distribution of density and assuming the solution to be of the form of progressive wave,we obtain a two-order nonlinear system.By means of this system,all results which were derived by Liu et al.(1984)were obtained.Moreover,it can be proved that there existed periodic solution in the nonlinear systems when there existed periodic solution in the one-order approxima- tion system,and some mathematic problems arising from series expansion were avoided.In this paper,a series of approximate solutions of nonlinear system is also discussed.
