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A crucial element for accurate EEG source reconstruction is the construction of a realistic head model, incorporating information on electrode positions and head tissue distribution. In this paper, we introduce MR-TIM, a toolbox for head tissue modelling from structural magnetic resonance (MR) images. The toolbox consists of three modules: 1) <jats:italic>image pre-processing<\/jats:italic> \u2013 the raw MR image is denoised and prepared for further analyses; 2) <jats:italic>tissue probability mapping<\/jats:italic> \u2013 template tissue probability maps (TPMs) in individual space are generated from the MR image; 3) <jats:italic>tissue segmentation<\/jats:italic> \u2013 information from all the TPMs is integrated such that each voxel in the MR image is assigned to a specific tissue. MR-TIM generates highly realistic 3D masks, five of which are associated with brain structures (brain and cerebellar grey matter, brain and cerebellar white matter, and brainstem) and the remaining seven with other head tissues (cerebrospinal fluid, spongy and compact bones, eyes, muscle, fat and skin). Our validation, conducted on MR images collected in healthy volunteers and patients\u00a0as well as an MR template image from an open-source repository, demonstrates that MR-TIM is more accurate than alternative approaches for whole-head tissue segmentation. We hope that MR-TIM, by yielding an increased precision in head modelling, will contribute to a more widespread use of EEG as a brain imaging technique.<\/jats:p>","DOI":"10.1007\/s12021-020-09504-5","type":"journal-article","created":{"date-parts":[[2021,1,27]],"date-time":"2021-01-27T20:02:40Z","timestamp":1611777760000},"page":"585-596","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Automated Head Tissue Modelling Based on Structural Magnetic Resonance Images for Electroencephalographic Source Reconstruction"],"prefix":"10.1007","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1989-6738","authenticated-orcid":false,"given":"Gaia Amaranta","family":"Taberna","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9799-9003","authenticated-orcid":false,"given":"Jessica","family":"Samogin","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6485-5559","authenticated-orcid":false,"given":"Dante","family":"Mantini","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,27]]},"reference":[{"issue":"21","key":"9504_CR1","doi-asserted-by":"publisher","first-page":"5011","DOI":"10.1088\/0031-9155\/49\/21\/012","volume":"49","author":"Z Akalin-Acar","year":"2004","unstructured":"Akalin-Acar, Z., & Gencer, N. 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