Kadir Kushsairy, Gao Hao, Payne Alex, Soraghan John, Berry Colin
Centre for excellence in Signal and Image Processing, Dept of Electronic and Electrical, University of Strathcylde, Glasgow G1 1XW, UK.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:8021-4. doi: 10.1109/IEMBS.2011.6091978.
Viability assessment of heart muscle after a myocardial infarction is an important step for diagnosis and therapy planning. It is important to quantify the area of edema because it can differentiate between viable and death myocardial tissues. In this paper an automatic method to quantify cardiac edema is presented. The method is based on a combination of morphological operations and statistical thresholding. Using real MRI data it is demonstrated that the proposed method can delineate edema region comparable to manual segmentation with a linear correlation coefficient r=0.76 and the mean difference is around 9.95%. The quantification result is also used to generate 3D visualisation model showing normal myocardial wall and edema region, which will enhance clinician diagnosis capability with real pattern of edema distribution and quantitative description.
心肌梗死后心肌活力评估是诊断和治疗规划的重要步骤。量化水肿区域很重要,因为它可以区分存活和死亡的心肌组织。本文提出了一种自动量化心脏水肿的方法。该方法基于形态学操作和统计阈值处理的结合。使用真实的MRI数据表明,所提出的方法能够勾勒出与手动分割相当的水肿区域,线性相关系数r = 0.76,平均差异约为9.95%。量化结果还用于生成显示正常心肌壁和水肿区域的3D可视化模型,这将通过水肿分布的真实模式和定量描述提高临床医生的诊断能力。