MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck
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{"title"=>"MIDA: A multimodal imaging-based detailed anatomical model of the human head and neck", "type"=>"journal", "authors"=>[{"first_name"=>"Maria Ida", "last_name"=>"Iacono", "scopus_author_id"=>"25321178800"}, {"first_name"=>"Esra", "last_name"=>"Neufeld", "scopus_author_id"=>"35243137100"}, {"first_name"=>"Esther", "last_name"=>"Akinnagbe", "scopus_author_id"=>"56460369000"}, {"first_name"=>"Kelsey", "last_name"=>"Bower", "scopus_author_id"=>"57197072510"}, {"first_name"=>"Johanna", "last_name"=>"Wolf", "scopus_author_id"=>"56459434400"}, {"first_name"=>"Ioannis Vogiatzis", "last_name"=>"Oikonomidis", "scopus_author_id"=>"36241836900"}, {"first_name"=>"Deepika", "last_name"=>"Sharma", "scopus_author_id"=>"55609434500"}, {"first_name"=>"Bryn", "last_name"=>"Lloyd", "scopus_author_id"=>"18037849500"}, {"first_name"=>"Bertram J.", "last_name"=>"Wilm", "scopus_author_id"=>"23101486000"}, {"first_name"=>"Michael", "last_name"=>"Wyss", "scopus_author_id"=>"7102423407"}, {"first_name"=>"Klaas P.", "last_name"=>"Pruessmann", "scopus_author_id"=>"6603694982"}, {"first_name"=>"Andras", "last_name"=>"Jakab", "scopus_author_id"=>"36473494400"}, {"first_name"=>"Nikos", "last_name"=>"Makris", "scopus_author_id"=>"35480152800"}, {"first_name"=>"Ethan D.", "last_name"=>"Cohen", "scopus_author_id"=>"57200427436"}, {"first_name"=>"Niels", "last_name"=>"Kuster", "scopus_author_id"=>"7003283774"}, {"first_name"=>"Wolfgang", "last_name"=>"Kainz", "scopus_author_id"=>"54924294700"}, {"first_name"=>"Leonardo M.", "last_name"=>"Angelone", "scopus_author_id"=>"7801510430"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"604612533", "issn"=>"19326203", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "doi"=>"10.1371/journal.pone.0124126", "scopus"=>"2-s2.0-84930670517", "pmid"=>"25901747", "sgr"=>"84930670517"}, "id"=>"2c3b492f-956b-3fea-9119-a840260e2827", "abstract"=>"Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named \"MIDA\". The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.", "link"=>"http://www.mendeley.com/research/mida-multimodal-imagingbased-detailed-anatomical-model-human-head-neck", "reader_count"=>87, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>6, "Student > Doctoral Student"=>5, "Researcher"=>26, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>4, "Other"=>7, "Student > Master"=>8, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>6, "Student > Doctoral Student"=>5, "Researcher"=>26, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>4, "Other"=>7, "Student > Master"=>8, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Engineering"=>30, "Unspecified"=>6, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>10, "Medicine and Dentistry"=>17, "Neuroscience"=>14, "Physics and Astronomy"=>2, "Psychology"=>3, "Computer Science"=>2, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>30}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>17}, "Neuroscience"=>{"Neuroscience"=>14}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Psychology"=>{"Psychology"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>10}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>6}}, "reader_count_by_country"=>{"United States"=>3, "Brazil"=>1, "United Kingdom"=>1, "Switzerland"=>1, "India"=>1}, "group_count"=>5}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2035667"], "description"=>"<p>Axial (left), coronal (middle), and sagittal (right) views of the T1- (top) and T2-weighted (bottom) structural MRIs. A specific T2-weighted MRI sequence with high nerve contrast optimized to enhance the structures of the ear and eye was also acquired (data not shown).</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391309, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g001", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Structural_MRI_scans_used_for_segmentation_/1391309", "title"=>"Structural MRI scans used for segmentation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035670"], "description"=>"<p>Axial view of maximum intensity projection from the 3D TOF (left) and the 3D PCA (middle) MRA. The TOF was optimized to highlight blood flowing in the cranial direction, i.e., mostly arteries, whereas the velocity window of the PCA was chosen such to highlight mostly veins. On the right an axial view of the principal eigenvector map is shown. In the color-coded fiber map, red, green, and blue represent the principal diffusion directions. It is possible to distinguish the corpus callosum in red with its fibers running mostly in left-right direction and the internal capsule bundle in blue with fibers running mostly in superior-inferior direction. Diffusion imaging is not directly used for the segmentation and generation of the anatomical model, but it provides anisotropic electrical properties of the tissues for electromagnetic applications and nerve orientation.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391312, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Vasculature_information_and_DTI_/1391312", "title"=>"Vasculature information and DTI.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035672"], "description"=>"<p>Sagittal view of the registered and integrated T1- and T2-weighted MRIs. The contrast between WM, e.g., corpus callosum, and GM signals is higher in T1, while the CSF, e.g., ventricle, is enhanced in T2. The tissue segmentation was performed by reaping the benefits of both MRI datasets.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391314, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g003", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_T1_and_T2_weighted_MRI_registration_/1391314", "title"=>"T1- and T2-weighted MRI registration.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035676"], "description"=>"<p>(a) Coronal section of the T2-weighted MRI centered on the nasal region, (b) the result of the automatic segmentation of the nasal mucosa, nasal septum, and air cavity by means of a region growing technique (step ii), (c) the result of the segmentation after the application of semi-automatic smoothing algorithms (step iii), and (d) the final segmentation result after manual delineation of the bone (not captured automatically) and global manual refinement (step iv).</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391318, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g004", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_procedure_/1391318", "title"=>"Segmentation procedure.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035685"], "description"=>"<p>Axial, coronal, and sagittal views of the outlines of the segmented head and neck structures (top row) and the color-coded label maps (bottom row).</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391320, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g005", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Final_segmentation_/1391320", "title"=>"Final segmentation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035686"], "description"=>"<p>3D reconstruction of a few representative structures of the head and neck. The muscles are shown with the skull structures. The vessels are shown both without and with the GM. The dura mater is shown on top of the brain and vessels.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391321, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g006", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_3D_Surfaces_/1391321", "title"=>"3D Surfaces.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035689"], "description"=>"<p>Examples of segmentation variability among operators A (yellow), B (red), and C (green) for a few representative structures of the head. (Bottom) Box plots of the values of the Dice (<i>D</i>) and modified Hausdorff distance (<i>MHD</i>) for the 35 structures are included in the analysis. The variability was assessed by comparing the segmentations of the operators with a consensus ground truth obtained using the STAPLE algorithm.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391324, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g007", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inter_operator_variability_/1391324", "title"=>"Inter-operator variability.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035691"], "description"=>"<p>Segmentation1 (yellow), Segmentation2 (red), and Segmentation3 (green) are provided for operators A, B and C on the top, middle, and bottom of the figure, respectively. The intra-operator variability was quantified asking each operator to repeat the segmentation of three selected structures (i.e., the globus pallidus, putamen, and thalamus) three times and measuring the similarity between the outlines performed by each user on different days and a consensus ground truth obtained using the STAPLE algorithm.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391326, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g008", "stats"=>{"downloads"=>2, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Intra_operator_variability_/1391326", "title"=>"Intra-operator variability.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035692"], "description"=>"<p>Comparison of two montages of stimulus electrode configurations. Sagittal view of the simulated magnitude of the electric field through the eye and of the current density stream lines for the (Fpz-Cz) montage (a) and the Cz-(Fz, C3, C4, Pz) montage (b). The first montage generated higher currents through the eye globe, which includes the retina, compared to the latter montage. (Bottom) Comparison of tissue-specific scalar vs. image-based tensorial electrical properties. Simulated magnitude of the electric field resulting from the (Fpz-Cz) montage tACS based on tissue-specific scalar electrical conductivity values (c) and DTI-based anisotropic values in brain tissues (d). DTI-based conductivity reduces the predicted field strength in the brain. The scale was set to dB (top) and linear (bottom) for visualization purposes.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391327, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g009", "stats"=>{"downloads"=>18, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_tACS_modeling_Top_/1391327", "title"=>"tACS modeling (Top).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035693"], "description"=>"<p>Coronal T1-weighted MRI (left) and outlines of the dura mater (right) with the principal dural reflections and sinuses. The falx cerebri, which separates the two cerebral hemispheres, was only partially visible on the images and was not segmented. The tentorium cerebelli was manually segmented. The superior sagittal sinus, transverse sinuses, and straight sinus—found along the attached edge of the falx, the line of attachment of the tentorium, and the line of attachment of the falx to the tentorium, respectively—were modeled as 500 μm thick outer layers enveloping the large venous vessels visible in the MRA dataset.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391328, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g010", "stats"=>{"downloads"=>0, "page_views"=>27, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_dura_mater_/1391328", "title"=>"Segmentation of the dura mater.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035694"], "description"=>"<p>(a) Original axial T1-weighted MRI, (b) intra-dural space obtained as the space surrounded by the previously segmented dura mater, (c) masked T1-weighted MRI, and (d) the image resulting from application of the <i>k</i>-means algorithm.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391329, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g011", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_cerebrum_/1391329", "title"=>"Segmentation of the cerebrum.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035695"], "description"=>"<p>Mid-coronal slice of the T1-weighted MRI (left) showing the CSF circulation (red arrows). Magnified view of the mid-coronal slice of the cerebellum (middle), showing the segmentation of the cerebellar GM (yellow) and WM (red). Mid-coronal slice of the brainstem and spinal cord (right), showing the landmarks used to subdivide the brainstem into its constituent substructures, i.e., the midbrain, pons, and medulla, and to separate the brainstem from the spinal cord.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391330, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g012", "stats"=>{"downloads"=>1, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_brainstem_cerebellum_and_CSF_/1391330", "title"=>"Segmentation of the brainstem, cerebellum, and CSF.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035698"], "description"=>"<p>Coronal slices of the deep brain structures from anterior to posterior (from a to i). Legend of the structures: 1 Caudate nucleus; 2 Lateral ventricles (anterior horn); 3 Internal capsule; 4 Nucleus accumbens; 5 Putamen; 6 Pallidum; 7 Third ventricle; 8 Amygdala; 9 External medullary lamina; 10 Lateral ventricles (body); 11 Lateral ventricles (inferior horn); 12 Lateral ventricles (collateral trigone); 13 Hippocampus (head); 14 Uncal sulcus; 15 Subiculum; 16 Uncinate gyrus; 17 Hippocampus (head)—gyrus dentatus; 18 Hippocampus (body)—gyrus dentatus; 19 Cornus ammonis; 20 Hippocampus (tail)—gyrus dentatus; 21 Cerebral aqueduct; 22 Fourth ventricle; 23 Optic nerve; 24 Pituitary gland and pituitary stalk or hypophysis and infundibulum; 25 Hypothalamus; 26 Mammillary body; 27 Pineal gland; 28 Anterior commissure; 29 Optic chiasm; 30 Optic tract; 31 Alveus; 32 Cisterna ambiens; 33 Parahippocampal gyrus; 34 Ansa peduncularis; 35 Entorhinal cortex. Right anterior oblique (j), left posterior oblique (k) and ventral caudal (l) view of the 3D reconstruction of the deep brain structures.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391332, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g013", "stats"=>{"downloads"=>2, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_deep_brain_structures_/1391332", "title"=>"Segmentation of deep brain structures.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035701"], "description"=>"<p>Axial (a), coronal (b) and sagittal (c) views of the individual and general muscle labels in the T1-weighted dataset. (d) Right anterior oblique view of the 3D reconstruction of the muscles. Legend of the structures: 1 Galea aponeurotica (tendon), 2 Skull, 3 Mandible, 4 Orbicularis oris, 5 Zygomaticus major, 6 Orbicularis oculi, 7 Muscles (general), 8 Depressor anguli oris, 9 Depressor labii inferioris, 10 Platysma, 11 Mentalis, 12 Buccinator, 13 Risorius, 14 Sternocleidomastoid, 15 Splenius capitis, 16 Trapezius, 17 Zygomaticus minor, 18 Temporalis & temporoparietalis, 19 Nasalis, 20 Procerus, 21 Occipitofrontalis frontal belly, 22 Occipitofrontalis occipital belly, 23 Masseter, 24 Levator scapulae, 25 Medial pterygoid, 26 Lateral pterygoid.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391334, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g014", "stats"=>{"downloads"=>1, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_muscles_/1391334", "title"=>"Segmentation of muscles.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035708"], "description"=>"<p>Top: coronal view of a T2-weighted MRI slice (a) with the skull, vertebrae, and intervertebral disks outlined (b). The T2-weighted MRI, in which the intensity of the cancellous bone inside the diploë is enhanced compared to that of the cortical bones of the inner and outer tables made the subdivision of the skull into the main three layers, i.e., outer table (white outline), diploë (yellow outline), and inner table (white outline) possible. Bottom: 3D reconstruction of the skull, vertebrae, and intervertebral disks (c and d).</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391341, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g015", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_bone_/1391341", "title"=>"Segmentation of the bone.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035710"], "description"=>"<p>T2 weighted axial, coronal and sagittal slab for the eye (left) and ear (right). The improved contrast allows for delineation of several thin substructures of the eye—e.g., optic nerve and lens—and ear—e.g., cochlea, semi-circular canals, and vestibulocochlear nerve—and the surrounding fat and fluids. 3D reconstruction (bottom) of the eye (left) and the ear (right) substructures.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391343, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g016", "stats"=>{"downloads"=>1, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_eye_and_ear_/1391343", "title"=>"Segmentation of the eye and ear.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035713"], "description"=>"<p>3D reconstruction of the 12 cranial nerves. Legend of the structures: Cranial Nerve I: Olfactory, Cranial Nerve II: Optic, Cranial Nerve III: Oculomotor, Cranial Nerve IV: Trochlear, Cranial Nerve V: Trigeminal, Cranial Nerve V2: Trigeminal Maxillary Division, Cranial Nerve V3: Trigeminal Mandibular Division, Cranial Nerve VI: Abducens, Cranial Nerve VII: Facial, Cranial Nerve VIII: Vestibulocochlear, Cranial Nerve IX: Glossopharyngeal, Cranial Nerve X: Vagus, Cranial Nerve XI: Accessory, Cranial Nerve XII: Hypoglossal.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391346, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g017", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_nerves_/1391346", "title"=>"Segmentation of the nerves.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035714"], "description"=>"<p>(Top) T1 weighted axial, coronal and sagittal view with the outline of the arteries (red) and veins (blue) and (Bottom) 3D reconstruction of the vessels. The arrows highlight the anterior and middle cerebral arteries, the basilar artery and the internal carotid which converge at the center to form the circle of Willis that supplies blood to the brain. Furthermore, the major veins are shown, including the dural venous sinuses running within the layers of the dura mater.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391347, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g018", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_vasculature_/1391347", "title"=>"Segmentation of the vasculature.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035715"], "description"=>"<p>Axial (a), coronal (b), sagittal (c), and 3D (d) views of the thalamus and nuclei. An automated atlas-based segmentation procedure was adopted to generate the map of the nuclei from the multiarchitectonic stereotactical atlas of the thalamus and to project them onto the head model.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391348, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.g019", "stats"=>{"downloads"=>3, "page_views"=>108, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Segmentation_of_the_thalamus_and_nuclei_/1391348", "title"=>"Segmentation of the thalamus and nuclei.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035716"], "description"=>"<p><sup>1</sup> Includes all the nuclei in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124126#pone.0124126.t002\" target=\"_blank\">Table 2</a>, excluding the Red nucleus (RN) and the Subthalamic nucleus (STh)</p><p>List of the segmented structures.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391349, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.t001", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_List_of_the_segmented_structures_/1391349", "title"=>"List of the segmented structures.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035717"], "description"=>"<p>Nuclei obtained via atlas-based segmentation.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391350, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.t002", "stats"=>{"downloads"=>5, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Nuclei_obtained_via_atlas_based_segmentation_/1391350", "title"=>"Nuclei obtained via atlas-based segmentation.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035718"], "description"=>"<p>Inter-operator variability across structures assessed on the axial slices.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391351, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.t003", "stats"=>{"downloads"=>4, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inter_operator_variability_across_structures_assessed_on_the_axial_slices_/1391351", "title"=>"Inter-operator variability across structures assessed on the axial slices.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035719"], "description"=>"<p>Inter-operator variability across structures assessed on the coronal slices.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391352, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.t004", "stats"=>{"downloads"=>7, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inter_operator_variability_across_structures_assessed_on_the_coronal_slices_/1391352", "title"=>"Inter-operator variability across structures assessed on the coronal slices.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035720"], "description"=>"<p>Inter-operator variability across structures assessed on the sagittal slices.</p>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391353, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126.t005", "stats"=>{"downloads"=>3, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inter_operator_variability_across_structures_assessed_on_the_sagittal_slices_/1391353", "title"=>"Inter-operator variability across structures assessed on the sagittal slices.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-04-22 03:42:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/2035721"], "description"=>"<div><p>Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1–2 mm and with 10–50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named “MIDA”. The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.</p></div>", "links"=>[], "tags"=>["nerve contrast optimized", "mra", "fiber orientation", "tissue types", "dti", "Neck Computational modeling", "brain structures", "discretization approaches", "Anatomical Model", "153 structures", "resonance angiography", "head model", "Human Head", "Diffusion tensor imaging", "skull layers", "mida", "resonance imaging", "Multiple voxel", "mri"], "article_id"=>1391354, "categories"=>["Biological Sciences"], "users"=>["Maria Ida Iacono", "Esra Neufeld", "Esther Akinnagbe", "Kelsey Bower", "Johanna Wolf", "Ioannis Vogiatzis Oikonomidis", "Deepika Sharma", "Bryn Lloyd", "Bertram J. Wilm", "Michael Wyss", "Klaas P. Pruessmann", "Andras Jakab", "Nikos Makris", "Ethan D. Cohen", "Niels Kuster", "Wolfgang Kainz", "Leonardo M. Angelone"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0124126", "stats"=>{"downloads"=>15, "page_views"=>35, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MIDA_A_Multimodal_Imaging_Based_Detailed_Anatomical_Model_of_the_Human_Head_and_Neck_/1391354", "title"=>"MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-04-22 03:42:26"}

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  • {"unique-ip"=>"30", "full-text"=>"32", "pdf"=>"11", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"68", "full-text"=>"120", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"31", "full-text"=>"66", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"29", "full-text"=>"29", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"17", "full-text"=>"18", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"15", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"19", "full-text"=>"13", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"14", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"26", "full-text"=>"24", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"21", "full-text"=>"47", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"59", "full-text"=>"74", "pdf"=>"13", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"80", "full-text"=>"101", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"74", "full-text"=>"134", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"62", "full-text"=>"92", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"61", "full-text"=>"102", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"12", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"53", "full-text"=>"78", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}

Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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