...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The international journal of lower extremity wounds >Can Thermal Imaging Technique be Used to Predict the Healing Status of a Venous Leg Ulcer?
【24h】

Can Thermal Imaging Technique be Used to Predict the Healing Status of a Venous Leg Ulcer?

机译：Can Thermal Imaging Technique be Used to Predict the Healing Status of a Venous Leg Ulcer?

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相关主题

摘要

Venous leg ulcers (VLUs) are the most common chronic wound types in older populations, with many wounds not healing in the normal trajectory. Many older people with wounds are treated in their homes, currently assessed by monitoring the wound area over weeks to ascertain the potential for healing. A noncontact method using thermal imaging has been shown to predict the healing trajectory of diabetes-related foot ulcers, although has not been tested in VLU or the home setting. This project investigated the effectiveness of using thermal imaging to predict VLU healing in the homes of participants. Images of 78 ulcers were collected weekly using a thermal camera from 67 participants in their homes, at 5 consecutive time points. Final follow-up calls were undertaken at 12 weeks to ascertain healing status (healed/unhealed). Images were preprocessed and segmented and the area of the region of the wound was extracted. Kruskal-Wallis tests were performed to test the association of the change of areas over the 5 consecutive weeks with the healing status of the ulcers at 12 weeks. The 95% confidence interval plots were obtained to study the distribution of the area in the healed and unhealed cases. This study found that the difference in the imaged areas between unhealed ulcers at 12 weeks did not reach statistical significance using thermal imaging. Therefore, thermal images could not predict healing progression in VLUs when the images were taken in the homes of participants. Future research to improve the prediction of venous leg ulcer healing should include developing a protocol to standardize conditions, improve imaging process methods, and use machine learning.

著录项

获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号