<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
The main contribution of this work is the careful syntactical definition of major white matter tracts in the human brain based on a neuroanatomist's expert knowledge. We present a technique to formally describe white matter tracts and to automatically extract them from diffusion MRI data. The framework is based on a novel query language with a near-to-English textual syntax. This query language allows us to construct a dictionary of anatomical definitions describing white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This enables automated coherent labeling of white matter anatomy across subjects. We use our method to encode anatomical knowledge in human white matter describing 10 association and 8 projection tracts per hemisphere and 7 commissural tracts. The technique is shown to be comparable in accuracy to manual labeling. We present results applying this framework to create a white matter atlas from 77 healthy subjects, and we use this atlas in a proof-of-concept study to detect tract changes specific to schizophrenia.
Models, Anatomic, Models, Neurological, Brain, Information Storage and Retrieval, Reproducibility of Results, Image Enhancement, Nerve Fibers, Myelinated, Sensitivity and Specificity, 004, Pattern Recognition, Automated, User-Computer Interface, Diffusion Tensor Imaging, Artificial Intelligence, Image Interpretation, Computer-Assisted, Humans, Natural Language Processing
Models, Anatomic, Models, Neurological, Brain, Information Storage and Retrieval, Reproducibility of Results, Image Enhancement, Nerve Fibers, Myelinated, Sensitivity and Specificity, 004, Pattern Recognition, Automated, User-Computer Interface, Diffusion Tensor Imaging, Artificial Intelligence, Image Interpretation, Computer-Assisted, Humans, Natural Language Processing
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 46 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |