| Item type |
デフォルトアイテムタイプ_（フル）(1) |
| 公開日 |
2024-12-16 |
| タイトル |
|
|
タイトル |
Development of a deep-learning algorithm for age estimation on CT images of the vertebral column |
|
言語 |
en |
| 作成者 |
Kawashita, Ikuo
Fukumoto, Wataru
Mitani, Hidenori
Narita, Keigo
Chosa, Keigo
Nakamura, Yuko
Nagao, Masataka
Awai, Kazuo
|
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利情報 |
|
|
言語 |
en |
|
権利情報 |
© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| 権利情報 |
|
|
言語 |
en |
|
権利情報 |
This is not the published version. Please cite only the published version. |
| 権利情報 |
|
|
言語 |
ja |
|
権利情報 |
この論文は出版社版ではありません。引用の際には出版社版をご確認、ご利用ください。 |
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Cadaver |
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Deep learning |
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
CT |
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Spine |
| 内容記述 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Purpose The accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on CT images of the vertebral column and checked its accuracy. Method For the development of our deep learning algorithm, we included 1,120 CT data of the vertebral column of 140 patients for each of 8 age decades. The deep learning model of regression analysis based on Visual Geometry Group-16 (VGG16) was improved in its estimation accuracy by bagging. To verify its accuracy, we applied our deep learning algorithm to estimate the age of 219 cadavers who had undergone postmortem CT (PMCT). The mean difference and the mean absolute error (MAE), the standard error of the estimate (SEE) between the known- and the estimated age, were calculated. Correlation analysis using the intraclass correlation coefficient (ICC) and Bland-Altman analysis were performed to assess differences between the known- and the estimated age. Results For the 219 cadavers, the mean difference between the known- and the estimated age was 0.30 years; it was 4.36 years for the MAE, and 5.48 years for the SEE. The ICC (2,1) was 0.96 (95 % confidence interval: 0.95–0.97, p < 0.001). Bland-Altman analysis showed that there were no proportional or fixed errors (p = 0.08 and 0.41). Conclusions Our deep learning algorithm for estimating the age of 219 cadavers on CT images of the vertebral column was more accurate than conventional methods and highly useful. |
|
言語 |
en |
| 出版者 |
|
|
出版者 |
Elsevier |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| 関連情報 |
|
|
関連タイプ |
isVersionOf |
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1016/j.legalmed.2024.102444 |
| 開始ページ |
|
|
開始ページ |
102444 |
| 書誌情報 |
en : Legal Medicine
巻 69,
p. 102444,
発行日 2024-04-07
|
| 旧ID |
55856 |
LegalMed_69_102444.pdf (5.3 MB)
