Name
Abstract | ||
|---|---|---|
Bone age assessment gives us evidence to analyze the children growth status and the rejuvenation involved chronological and biological ages. All the previous works consider left-hand X-ray image of a child in their works. In this paper, we carry out a study on estimating human age using whole-body bone CT images and a novel convolutional neural network. Our model with additional connections shows an effective way to generate a massive number of vital features while reducing overfitting influence on small training data in the medical image analysis research area. A dataset and a comparison with common deep architectures will be provided for future research in this field. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Computer Vision and Pattern Recognition | Journal |
Volume | Citations | PageRank |
abs/1901.10237 | 0 | 0.34 |
References | Authors | |
11 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hai Duong Nguyen | 1 | 5 | 2.82 |
| Soo-Hyung Kim | 2 | 191 | 49.03 |