首页> 外文会议>Digital Society, 2010. ICDS '10 >Intelligent e-Tools for Wound Image Understanding and Evaluation
【24h】

Intelligent e-Tools for Wound Image Understanding and Evaluation

机译:用于伤口图像理解和评估的智能电子工具

获取原文

摘要

This paper presents a Java framework for analyzing, processing and understanding wound images, to be used in teaching, learning and research activities. We intend to promote e-learning technologies in medical, pharmaceutical and health care domains. Using Java and XML technologies, we build models for various categories of wounds, due to various etiologies. Based on color and texture analysis, we identify the main barriers to wound healing, such as tissue nonviable, infection, inflammation, moisture imbalance, or edge non-advancing. This framework provides the infrastructure for preparing e-learning scenarios based on practice and real world experiences. We make experiments for wound healing simulation using various treatments and compare the results with experimental observations. Our experiments are supported by XML based databases containing knowledge extracted from previous wound healing experiences and from medical experts' knowledge. Also, we rely on new paradigms of the Artificial Intelligence for creating e-learning scenarios to be used in a context of active learning, for wound image understanding. To implement the e-learning tools, we use Java technologies for dynamic processes and XML technologies for dynamic content. Our approach to e-learning is so called blended learning, which combines traditional face-to-face and Web-based on-line learning, with focus on principles of active learning.
机译:本文提出了一个用于分析,处理和理解伤口图像的Java框架,该框架将用于教学,学习和研究活动中。我们打算在医学,制药和保健领域推广电子学习技术。由于各种病因,我们使用Java和XML技术为各种伤口建立了模型。基于颜色和纹理分析,我们确定了伤口愈合的主要障碍,例如组织不可行,感染,炎症,水分失衡或边缘不进展。该框架提供了基于实践和实际经验来准备电子学习方案的基础结构。我们使用各种治疗方法进行伤口愈合模拟实验,并将结果与​​实验观察结果进行比较。我们的实验得到基于XML的数据库的支持,该数据库包含从以前的伤口愈合经验和医学专家的知识中提取的知识。此外,我们依靠人工智能的新范式创建电子学习场景,以用于主动学习的环境中,以了解伤口图像。为了实现电子学习工具,我们将Java技术用于动态流程,将XML技术用于动态内容。我们的电子学习方法称为混合学习,它结合了传统的面对面学习和基于Web的在线学习,并着重于主动学习的原则。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
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