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A Novel Human Brainstem Map Based on True-Color Sectioned Images

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Background Existing atlases for the human brainstem were generated from magnetic resonance images or traditional histologically stained slides, but both are insufficient for the identification of detailed brainstem structures at… Click to show full abstract

Background Existing atlases for the human brainstem were generated from magnetic resonance images or traditional histologically stained slides, but both are insufficient for the identification of detailed brainstem structures at uniform intervals. Methods A total of 319 sectioned images of the brainstem were selected from whole-body axial sectioned images, then coronal and sagittal sectioned images were reconstructed from the horizontal images. The fine and detailed structures were annotated in PowerPoint slides, then the volume model was produced and some white matter fibers were traced using MRIcroGL. Results In this study, a novel brainstem atlas based on sectioned images was generated that shows the true color and shape, as well as the accurate location of the nuclei and tracts; it reveals the striking contrast between gray and white matter, as well as fine structures. In total, 212 structures, including nuclei and tracts, were annotated in axial, coronal, and sagittal plane views of sectioned images (48-bit true color; 0.2 mm intervals, 0.06 mm × 0.06 mm pixel size). To verify the accuracy of the annotations, a volume model of the brainstem was constructed for independent observations of the three planes. Conclusion In this paper, we describe several interesting structures included in the atlas. By depicting the fine structures of the human brainstem in detail, this atlas allows comprehensive understanding of the complicated topographies of the brainstem. As such, it will be of value for neuroanatomy education and research, in addition to enriching the literature on the human brain.

Keywords: brainstem; sectioned images; novel human; true color; human brainstem

Journal Title: Journal of Korean Medical Science
Year Published: 2023

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