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首页> 外文会议>Conference on physiology and function from multidimensional images >Identification of atherosclerotic plaque components using cluster analysis of multispectral MR images: comparison with histology
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Identification of atherosclerotic plaque components using cluster analysis of multispectral MR images: comparison with histology

机译：利用多光谱MR图像聚类分析鉴定动脉粥样硬化斑块组分：与组织学相比

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The composition of atherosclerotic lesions in the carotid arteries is believed to be an important predictor of stroke risk. Several MR contrasts may be necessary to discriminate between different plaque components, and multispectral analysis can used to integrate the information obtained from these multiple contrasts. This study presents the use of registered MR and histological images of carotid endarterectomy specimens as a tool for the quantitative assessment of maximum likelihood classification and other segmentation algorithms. Carotid endarterectomy specimens were imaged in a 1.5T GE Signa scanner. PD, T1, T2, diffusion spin echo weightings were obtained. MR images were registered with digitized images of the corresponding histology. A pathologist identified regions of collagen, calcification, cholesterol, hemorrhage on the histological images. Training and ground truth regions were selected. The accuracy of the maximum likelihood classification was assessed on a pixel by pixel basis using truth regions identified on histological images. The accuracy of multispectral analysis was calcification (73%), fibrin (68%), cholesterol (62%), fibrous plaque (53%). This technique was limited by registration inaccuracies caused by partial volume effects and histological artifacts. Despite these limitations, accuracy results were reasonable. This technique, with continued improvements, provides a framework for evaluating the accuracy of different segmentation algorithms.
机译：颈动脉动脉中动脉粥样硬化病变的组成被认为是卒中风险的重要预测因子。可能需要几个MR对比度来区分不同斑块组分，并且多光谱分析可以用于集成从这些多个对比度获得的信息。本研究表明，使用颈动脉胚胎切除术标本的注册MR和组织学图像作为最大似然分类和其他分段算法的定量评估的工具。在1.5T GE Signa扫描仪中成像颈动脉内膜切除术。获得Pd，T1，T2，扩散旋转回波加权。 MR图像被登记为相应组织学的数字化图像。病理学家确定了胶原蛋白，钙化，胆固醇，组织学图像出血的区域。选择了培训和地面真理地区。使用在组织学图像上识别的真理区域对像素的像素基础评估最大似然分类的准确性。多光谱分析的准确性是钙化（73％），纤维蛋白（68％），胆固醇（62％），纤维状斑块（53％）。该技术受部分体积效应和组织学伪影引起的注册不准确性的限制。尽管有这些限制，但准确的结果是合理的。这种具有持续改进的技术提供了一种用于评估不同分段算法的准确性的框架。

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