Abstract
For the quantitative analysis of medical images in clinical research, diagnosis and treatment, a reliable basic framework for developing a normal human ear atlas of voxel-based computed tomography (CT) images was proposed. We annotated 10 precise ear structures with different labels from 64 patients with normal ear structures. Paired-samples t test, Pearson’s test and descriptive statistics were carried on the volume and coordinate data, which were first obtained from annotation to verify the correlation and difference. In addition, we constructed a three dimensional (3D) model of the standard human ear atlas with six views for presentation. Through a series of statistical analyses, a standard 3D normal human ear atlas containing volume and spatial data was obtained from voxel-based CT images. There was a significant negative correlation exists between age and the volume of the incus, and no correlation with other structures. There was no significant correlation between slice thickness and the volume of 10 structures. The volume of most structures on both sides is significantly correlated and there was no significant difference in the volume of most structures on both sides except for the jugular foramen. Besides, the coordinate range of the bilateral structures is relatively consistent. The specific volume and spatial data for the human ear atlas are helpful in the diagnosis of abnormalities, and this 3D normal human ear atlas will provide new insights for radiologists in clinical research.
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Abbreviations
- CT:
-
Computed tomography
- 3D:
-
Three dimensional
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Acknowledgements
The work in this paper was supported by the Science and Technology Development Program of Beijing Education Committee (No. KM201810005026), the National Natural Science Foundation of China (No. 61871006), the National Natural Science Foundation of China (No. 61527807), Beijing Scholar 2015, and Beijing Municipal Administration of Hospitals’ Mission Plan (No. SML20150101).
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Zhang, Y., Zhang, H., Zhuo, L. et al. A 3D Normal Human Ear Atlas of Voxel-Based CT Images. Sens Imaging 20, 19 (2019). https://doi.org/10.1007/s11220-019-0238-y
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DOI: https://doi.org/10.1007/s11220-019-0238-y