RANKING AND CLASSIFICATION OF MONOTONIC EMPHYSEMA PATTERNS WITH A MULTI-CLASS HIERARCHICAL APPROACH.
RANKING AND CLASSIFICATION OF MONOTONIC EMPHYSEMA PATTERNS WITH A MULTI-CLASS HIERARCHICAL APPROACH.
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使用多类分层方法对单调肺气肿模式进行排序和分类。
DOI：
10.1109/isbi.2014.6868049
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Estepar,RaulSanJose
中科院分区：
文献类型：
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作者：
Kurugol,Sila;Washko,GeorgeR;Estepar,RaulSanJose
肺气肿有明显的和明确的视觉上明显的CT模式，称为小叶中心和全小叶肺气肿。现有的研究集中在这些模式的分类，但他们没有看到这种疾病的完整演变，因为肺实质的破坏从正常肺组织进展到轻度，中度和重度疾病，肺结构完全消失。在本文中，我们将这个连续的过程离散成五类疾病的严重程度不断增加，并构建了一个训练集的1161 CT补丁。我们利用三个解决方案，这个单调的多类分类问题：一个全球rankSVM的排名，分层SVM分类和这两个的组合，我们称之为分层rankSVM。结果表明，这两个层次的方法是计算效率。分级SVM的分类精度稍好。然而，除了分类之外，排序方法还提供了模式的排序，其可以用作连续疾病进展评分。在分类精度和成对约束满足率方面，分层rankSVM优于全局rankSVM。
Emphysema has distinct and well-defined visually apparent CT patterns called centrilobular and panlobular emphysema. Existing studies concentrated on the classification of these patterns but they have not looked at the complete evolution of this disease as the destruction of lung parenchyma progresses from normal lung tissue to mild, moderate, and severe disease with complete effacement of the lung architecture. In this paper, we discretize this continuous process into five classes of increasing disease severity and construct a training set of 1161 CT patches. We exploit three solutions to this monotonic multi-class classification problem: a global rankSVM for ranking, hierarchical SVM for classification and a combination of these two, which we call a hierarchical rankSVM. Results showed that both hierarchical approaches were computationally efficient. The classification accuracies were slightly better for hierarchical SVM. However, in addition to classification, ranking approaches also provided a ranking of patterns, which can be utilized as a continuous disease progression score. In terms of the classification accuracy and ratio of pair-wise constraints satisfied, hierarchical rankSVM outperformed the global rankSVM.