Dataset Information

Deep Learning-Based CT Radiomics for Feature Representation and Analysis of Aging Characteristics of Asian Bony Orbit.

ABSTRACT:

Objective

This paper puts forward a new method for automatic segmentation of bony orbit as well as automatic extraction and classification of aging features of segmented orbit contour based on depth learning, with which the aging mode of bony orbit contour is preliminarily validated.

Method

Three-dimensional reconstruction was carried out by using the craniofacial Computed Tomography scanning data of 595 adult Mongolians at different ages (119 young males, 78 young females, 109 middle-aged males, 89 middle-aged females, 95 elderly males, and 105 elderly females), the craniofacial images were exported, orbit contour images were obtained with U-Net segmentation network, and then the orbit contour features of young group, the middle-aged group and the elderly group were classified with the classification network. Next, contour area, height, and other features put forward in existing research were automatically calculated by using the connected component shape description method; and it was validated whether the aging features of the bony orbit only occur to partial or the whole orbit.

Results

With the method put forward in this paper, high-precision identification (97.94% and 99.18%) of 3 categories in the male and female group experiments. In the meanwhile, it was found in the comparison experiment with other features that bony orbit contour definitely has features relating to aging, but these features only occur to partial areas of the orbit, which enables the convolutional neural network to achieve good identification effects. And, bone resorption of the superior orbital rim of males is more obvious than that of the inferior orbital rim, but the overall shape features like the bony orbit area and height do not change significantly along with the increase of the age.

Conclusions

U-Net can realize high-precision segmentation of the orbit contour, and with the Convolutional Neural Network-based orbit contour sorting algorithm, the aging degree of the bony orbit can be identified precisely. It is preliminarily validated that the aging mode of Mongolian bony orbit contour is that the bone resorption of the superior orbital rim is more obvious than that of the inferior orbital rim, and the change of the orbit area, perimeter, height and circularity is not obvious in the aging process.

SUBMITTER: Li Z

PROVIDER: S-EPMC8694253 | biostudies-literature |

REPOSITORIES: biostudies-literature

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