Case-based tissue classification for monitoring leg ulcer healing

M. Galushka, Huiru Zheng, D. Patterson, L. Bradley
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引用次数: 37

Abstract

The ability to automatically monitor the wound healing process would reduce the workload of professionals, provide standardization, reduce costs, and improve the quality of care for patients. Here we propose an automatic monitoring system for leg ulcers based on case-based reasoning. We focus on the first stage of the monitoring process in this work, that of tissue classification and examine a number of different feature extraction techniques based on texture and Red, Green, and Blue histograms. Results clearly show a case-based approach to be ideal for this type of task.
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基于病例的组织分类监测腿部溃疡愈合
自动监测伤口愈合过程的能力将减少专业人员的工作量,提供标准化,降低成本,并提高患者的护理质量。在此,我们提出一种基于案例推理的腿部溃疡自动监测系统。在这项工作中,我们专注于监测过程的第一阶段,即组织分类,并研究了基于纹理和红、绿、蓝直方图的许多不同的特征提取技术。结果清楚地表明,基于案例的方法是理想的这种类型的任务。
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Markov model-based clustering for efficient patient care Incremental learning of ensemble classifiers on ECG data Grid-enabled workflows for data intensive medical applications Case-based tissue classification for monitoring leg ulcer healing Optimisation of neural network training through pre-establishment of synaptic weights applied to body surface mapping classification
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