Accurate anatomical head segmentations: a data set for biomedical simulations

Silvia Farcito, Oula Puonti, Hazael Montanaro, Guilherme B. Saturnino, Jesper Duemose Nielsen, Camilla G. Madsen, Hartwig R. Siebner, Esra Neufeld, Niels Kuster, Bryn A. Lloyd, Axel Thielscher

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Detailed computational anatomical models of the entire head are needed for accurate in silico modeling in a variety of transcranial stimulation applications. Models from different subjects help to understand and account for population variability. To this end, we have developed a new library of head models of 20 individuals, segmented from co-aligned multi-modal medical image data. The acquired image modalities allow to accurately model tissues with different material properties, such as electrical conductivity or spatially varying acoustic properties. The usefulness of the models is illustrated for two example applications.
Original languageEnglish
Title of host publicationProceedings of 39th Annual International Conference of the Ieee Engineering in Medicine and Biology Society
Number of pages6
PublisherIEEE
Publication date2019
Pages6118-6123
DOIs
Publication statusPublished - 2019
Event2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society - CityCube Berlin, Berlin, Germany
Duration: 23 Jul 201927 Jul 2019
https://embc.embs.org/2019/

Conference

Conference2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
LocationCityCube Berlin
CountryGermany
CityBerlin
Period23/07/201927/07/2019
Internet address

Cite this

Farcito, S., Puonti, O., Montanaro, H., Saturnino, G. B., Nielsen, J. D., Madsen, C. G., Siebner, H. R., Neufeld, E., Kuster, N., Lloyd, B. A., & Thielscher, A. (2019). Accurate anatomical head segmentations: a data set for biomedical simulations. In Proceedings of 39th Annual International Conference of the Ieee Engineering in Medicine and Biology Society (pp. 6118-6123). IEEE. https://doi.org/10.1109/EMBC.2019.8857041