A representation and classification scheme for tree-like structures in medical images: analyzing the branching pattern of ductal trees in X-ray galactograms.
A representation and classification scheme for tree-like structures in medical images: analyzing the branching pattern of ductal trees in X-ray galactograms.
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DOI：
10.1109/tmi.2008.929102
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发表时间：
2009-04
影响因子：
10.6
通讯作者：
Maidment AD
中科院分区：
文献类型：
--
作者：
Megalooikonomou V;Barnathan M;Kontos D;Bakic PR;Maidment AD
我们提出了一种多步骤的方法来表示和分类医学图像中的树状结构。树形结构在生物医学领域经常遇到；例如支气管系统、血管拓扑结构和乳腺导管网络。我们使用树编码技术，如深度优先字符串编码和pr<s:1> fer编码，以获得树的分支拓扑的符号字符串表示；然后将树分类问题简化为字符串分类。我们使用tf-idf文本挖掘技术为每个字符串术语（即树节点标签）分配重要权重。使用tf-idf权重向量和余弦相似度度量执行树的相似性搜索和k近邻分类。为了区分不同的影像学表现，我们应用了我们的方法来表征x射线星系图上的导管树状实质结构。实验结果证明了该方法的有效性，分类准确率高达86%，也表明我们的方法可能有助于深入了解分支模式与功能或病理之间的关系。
We propose a multistep approach for representing and classifying tree-like structures in medical images. Tree-like structures are frequently encountered in biomedical contexts; examples are the bronchial system, the vascular topology, and the breast ductal network. We use tree encoding techniques, such as the depth-first string encoding and the Prüfer encoding, to obtain a symbolic string representation of the tree's branching topology; the problem of classifying trees is then reduced to string classification. We use the tf-idf text mining technique to assign a weight of significance to each string term (i.e., tree node label). Similarity searches and k-nearest neighbor classification of the trees is performed using the tf-idf weight vectors and the cosine similarity metric. We applied our approach to characterize the ductal tree-like parenchymal structure in X-ray galactograms, in order to distinguish among different radiological findings. Experimental results demonstrate the effectiveness of the proposed approach with classification accuracy reaching up to 86%, and also indicate that our method can potentially aid in providing insight to the relationship between branching patterns and function or pathology.