1. | A. Stanziola; J. A. Pineda-Pardo; B. E. Treeby Transcranial ultrasound simulation with uncertainty estimation Journal Article In: JASA Express Letters, 3 (5), pp. 052001, 2023. Links | BibTeX @article{2023-Stanziola-JASAEL-Uncertainty,
title = {Transcranial ultrasound simulation with uncertainty estimation},
author = {A. Stanziola and J. A. Pineda-Pardo and B. E. Treeby},
url = {http://bug.medphys.ucl.ac.uk/papers/2023-Stanziola-JASAEL-2},
doi = {10.1121/10.0019380},
year = {2023},
date = {2023-05-11},
journal = {JASA Express Letters},
volume = {3},
number = {5},
pages = {052001},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
2. | A. Stanziola; S. R. Arridge; B. T. Cox; B. E. Treeby A learned Born series for highly-scattering media Journal Article In: JASA Express Letters, 3 (5), pp. 052401, 2023. Links | BibTeX @article{2023-Stanziola-JASAEL,
title = {A learned Born series for highly-scattering media},
author = {A. Stanziola and S. R. Arridge and B. T. Cox and B. E. Treeby},
url = {http://bug.medphys.ucl.ac.uk/papers/2023-Stanziola-JASAEL.pdf},
doi = {10.1121/10.0017937},
year = {2023},
date = {2023-05-01},
journal = {JASA Express Letters},
volume = {3},
number = {5},
pages = {052401},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
3. | A. Stanziola; S. R. Arridge; B. T. Cox; B. E. Treeby j-Wave: An open-source differentiable wave simulator Journal Article In: SoftwareX, 22 , pp. 101338, 2023. Abstract | Links | BibTeX @article{2023-Stanziola-SoftwareX,
title = {j-Wave: An open-source differentiable wave simulator},
author = {A. Stanziola and S. R. Arridge and B. T. Cox and B. E. Treeby},
url = {http://bug.medphys.ucl.ac.uk/papers/2023-Stanziola-SoftwareX.pdf
},
doi = {10.1016/j.softx.2023.101338},
year = {2023},
date = {2023-02-07},
journal = {SoftwareX},
volume = {22},
pages = {101338},
abstract = {We present an open-source differentiable acoustic simulator, j-Wave, which can solve time-varying and time-harmonic acoustic problems. It supports automatic differentiation, which is a program transformation technique that has many applications, especially in machine learning and scientific computing. j-Wave is composed of modular components that can be easily customized and reused. At the same time, it is compatible with some of the most popular machine learning libraries, such as JAX and TensorFlow. The accuracy of the simulation results for known configurations is evaluated against the widely used k-Wave toolbox and a cohort of acoustic simulation software. j-Wave is available from https://github.com/ucl-bug/jwave.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present an open-source differentiable acoustic simulator, j-Wave, which can solve time-varying and time-harmonic acoustic problems. It supports automatic differentiation, which is a program transformation technique that has many applications, especially in machine learning and scientific computing. j-Wave is composed of modular components that can be easily customized and reused. At the same time, it is compatible with some of the most popular machine learning libraries, such as JAX and TensorFlow. The accuracy of the simulation results for known configurations is evaluated against the widely used k-Wave toolbox and a cohort of acoustic simulation software. j-Wave is available from https://github.com/ucl-bug/jwave. |
4. | M. Miscouridou; J. A. Pineda-Pardo; C. J. Stagg; B. E. Treeby; A. Stanziola Classical and Learned MR to Pseudo-CT Mappings for Accurate Transcranial Ultrasound Simulation Journal Article In: IEEE Transactions of Ultrasonics, Ferroelectrics, and Frequency Control, 69 (10), pp. 2896-2905, 2022. Links | BibTeX @article{2022-Miscouridou-IEEETUFFC,
title = {Classical and Learned MR to Pseudo-CT Mappings for Accurate Transcranial Ultrasound Simulation},
author = {M. Miscouridou and J. A. Pineda-Pardo and C. J. Stagg and B. E. Treeby and A. Stanziola},
url = {http://bug.medphys.ucl.ac.uk/papers/2022-Miscouridou-IEEETUFFC.pdf
},
doi = {10.1109/TUFFC.2022.3198522},
year = {2022},
date = {2022-08-06},
journal = {IEEE Transactions of Ultrasonics, Ferroelectrics, and Frequency Control},
volume = {69},
number = {10},
pages = {2896-2905},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
5. | J-F. Aubry; O. Bates; C. Boehm; K. Butts Pauly; D. Christensen; C. Cueto; P. Gélat; L. Guasch; J. Jaros; Y. Jing; R. Jones; N. Liu; P. Marty; H. Montanaro; E. Neufeld; S. Pichardo; G. Pinton; A. Pulkkinen; A. Stanziola; A. Thielscher; B. E. Treeby; E. van t'Wout Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models Journal Article In: J. Acoust. Soc. Am., 152 (2), pp. 1004–1019, 2022. Links | BibTeX @article{2022-Aubry-JASA,
title = {Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models},
author = {J-F. Aubry and O. Bates and C. Boehm and K. Butts Pauly and D. Christensen and C. Cueto and P. Gélat and L. Guasch and J. Jaros and Y. Jing and R. Jones and N. Liu and P. Marty and H. Montanaro and E. Neufeld and S. Pichardo and G. Pinton and A. Pulkkinen and A. Stanziola and A. Thielscher and B. E. Treeby and E. van t'Wout},
url = {http://bug.medphys.ucl.ac.uk/papers/2022-Aubry-JASA},
doi = {10.1121/10.0013426},
year = {2022},
date = {2022-07-22},
journal = {J. Acoust. Soc. Am.},
volume = {152},
number = {2},
pages = {1004–1019},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
6. | A. Stanziola; S. R. Arridge; B. T. Cox; B. E. Treeby A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound Journal Article In: J. Comput. Phys., 441 , pp. 110430, 2021. Links | BibTeX @article{2021-Stanziola-JCP,
title = {A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound},
author = {A. Stanziola and S. R. Arridge and B. T. Cox and B. E. Treeby},
url = {http://bug.medphys.ucl.ac.uk/papers/2021-Stanziola-JCP.pdf},
doi = {10.1016/j.jcp.2021.110430},
year = {2021},
date = {2021-05-21},
journal = {J. Comput. Phys.},
volume = {441},
pages = {110430},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|