使用计算机视觉和人工智能来追踪严重烧伤的愈合
Olivier Ethier1, Hannah O Chan2,3, Mahla Abdolahnejad2
1Montreal Institute of Learning Algorithms (MILA), University of Montreal, Montreal, QC H2S 3H1, Canada.
概括
人工智能和计算机视觉为烧伤严重程度分类和伤口愈合跟踪提供了新的工具. 这项技术可以实现远程患者监测和改进的临床评估,以更好地管理烧伤护理.
科学领域:
- 医疗技术 医学技术
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 准确的烧伤严重程度评估对于有效的治疗至关重要,特别是区分表面和深部部分厚度烧伤.
- 在亚急性护理中,持续监测伤口愈合是预防并发症的关键.
- 现有的燃烧评估和跟踪方法可能资源密集,可能缺乏持续监测能力.
研究的目的:
- 开发和评估基于人工智能 (AI) 和计算机视觉 (CV) 的管道,用于分类烧伤严重程度和追踪伤口愈合.
- 为临床和远程患者使用创建可访问,低成本的工具.
- 为了证明使用图像引导治疗用于伤口参数评估的可行性.
主要方法:
- 基于AI-CV的皮肤异常跟踪算法管道的开发.
- 使用高质量的2D彩色图像进行伤口评估.
- 追踪关键的伤口参数,包括2D空间尺寸和颜色变化,表明愈合或并发症.
主要成果:
- 人工智能-CV管道成功分类了烧伤严重程度,并跟踪了伤口愈合.
- 通过图像分析,证明了通过伤口内的生理变化进行表征的能力.
- 成功追踪一个单一的烧伤8周 (6周诊所,2周家庭监测).
结论:
- 人工智能和CV为客观和可访问的烧伤护理管理提供了一个有希望的方法.
- 开发的算法可以帮助临床医生评估烧伤严重程度和监测愈合进展.
- 这项技术支持持续的伤口跟踪,通过早期并发症检测和远程护理,有可能改善患者的治疗结果.
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