The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Electric field calculations in brain stimulation based on finite elements: An optimized processing pipeline for the generation and usage of accurate individual head models
Open accessAbstract
The need for realistic electric field calculations in human noninvasive brain stimulation is undisputed to more accurately determine the affected brain areas. However, using numerical techniques such as the finite element method (FEM) is methodologically complex, starting with the creation of accurate head models to the integration of the models in the numerical calculations. These problems substantially limit a more widespread application of numerical methods in brain stimulation up to now. We introduce an optimized processing pipeline allowing for the automatic generation of individualized high‐quality head models from magnetic resonance images and their usage in subsequent field calculations based on the FEM. The pipeline starts by extracting the borders between skin, skull, cerebrospinal fluid, gray and white matter. The quality of the resulting surfaces is subsequently improved, allowing for the creation of tetrahedral volume head meshes that can finally be used in the numerical calculations. The pipeline integrates and extends established (and mainly free) software for neuroimaging, computer graphics, and FEM calculations into one easy‐to‐use solution. We demonstrate the successful usage of the pipeline in six subjects, including field calculations for transcranial magnetic stimulation and transcranial direct current stimulation. The quality of the head volume meshes is validated both in terms of capturing the underlying anatomy and of the well‐shapedness of the mesh elements. The latter is crucial to guarantee the numerical robustness of the FEM calculations. The pipeline will be released as open‐source, allowing for the first time to perform realistic field calculations at an acceptable methodological complexity and moderate costs. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.
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Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
Nitsche, M. A., & Paulus, W. (2000) · The Journal of Physiology · doi:10.1111/j.1469-7793.2000.t01-1-00633.x · Cited by 5,656
Cited by
Thielscher, A., Antunes, A., & Saturnino, G. B. (2015) · 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7318340 · Cited by 942
Self-citationNeymotin, S. A., Daniels, D. S., Caldwell, B., McDougal, R. A., Carnevale, N. T., Jas, M., Moore, C. I., Hines, M. L., Hämäläinen, M., & Jones, S. R. (2020) · eLife · doi:10.7554/elife.51214 · Cited by 109
Wenger, C., Salvador, R., Basser, P. J., & Miranda, P. C. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/18/7339 · Cited by 121
Hill, A. T., Rogasch, N. C., Fitzgerald, P. B., & Hoy, K. E. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.03.001 · Cited by 105
Albizu, A., Fang, R., Indahlastari, A., O’Shea, A., Stolte, S. E., See, K. B., Boutzoukas, E. M., Kraft, J. N., Nissim, N. R., & Woods, A. J. (2020) · Brain Stimulation · doi:10.1016/j.brs.2020.10.001 · Cited by 79
Metadata
- Authors
- Windhoff, M., Opitz, A., & Thielscher, A.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2011-11-23
- Volume
- 34
- Issue
- 4
- Pages
- 923-935
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2127919130
- Cited by
- 441
- References
- 2
- FWCI
- 5.19
- Type
- journal article
- Language
- en
- Open access
- green
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