一种基于伤口面积测定、颜色分割和愈合评分评估的糖尿病足溃疡自动评估系统。
An Automatic Assessment System of Diabetic Foot Ulcers Based on Wound Area Determination, Color Segmentation, and Healing Score Evaluation.
作者信息
Wang Lei, Pedersen Peder C, Strong Diane M, Tulu Bengisu, Agu Emmanuel, Ignotz Ron, He Qian
机构信息
Electrical and Computer Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA
Electrical and Computer Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA.
出版信息
J Diabetes Sci Technol. 2015 Aug 7;10(2):421-8. doi: 10.1177/1932296815599004.
BACKGROUND
For individuals with type 2 diabetes, foot ulcers represent a significant health issue. The aim of this study is to design and evaluate a wound assessment system to help wound clinics assess patients with foot ulcers in a way that complements their current visual examination and manual measurements of their foot ulcers.
METHODS
The physical components of the system consist of an image capture box, a smartphone for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image.
RESULTS
The system was evaluated by assessing foot ulcers for 12 patients in the Wound Clinic at University of Massachusetts Medical School. As performance measures, the Matthews correlation coefficient (MCC) value for the wound area determination algorithm tested on 32 foot ulcer images was .68. The clinical validity of our healing score algorithm relative to the experienced clinicians was measured by Krippendorff's alpha coefficient (KAC) and ranged from .42 to .81.
CONCLUSION
Our system provides a promising real-time method for wound assessment based on image analysis. Clinical comparisons indicate that the optimized mean-shift-based algorithm is well suited for wound area determination. Clinical evaluation of our healing score algorithm shows its potential to provide clinicians with a quantitative method for evaluating wound healing status.
背景
对于2型糖尿病患者而言，足部溃疡是一个重大的健康问题。本研究的目的是设计并评估一种伤口评估系统，以帮助伤口诊所评估足部溃疡患者，从而补充其当前对足部溃疡的目视检查和手动测量。
方法
该系统的物理组件包括一个图像采集箱、一部用于采集伤口图像的智能手机以及一台用于分析伤口图像的笔记本电脑。伤口图像评估算法可计算伤口总面积、颜色分割的伤口区域以及愈合评分，以便对单个伤口图像的伤口愈合状态进行定量评估，并将后续图像与初始伤口图像进行比较。
结果
通过对马萨诸塞大学医学院伤口诊所的12名患者的足部溃疡进行评估，对该系统进行了评价。作为性能指标，在32张足部溃疡图像上测试的伤口面积测定算法的马修斯相关系数（MCC）值为0.68。我们的愈合评分算法相对于经验丰富的临床医生的临床有效性通过克里彭多夫阿尔法系数（KAC）进行衡量，范围在0.42至0.81之间。
结论
我们的系统提供了一种基于图像分析的、有前景的实时伤口评估方法。临床比较表明，优化后的基于均值漂移的算法非常适合伤口面积测定。我们的愈合评分算法的临床评估表明，它有潜力为临床医生提供一种评估伤口愈合状态的定量方法。
Zotero 插件