Tschirren Juerg, McLennan Geoffrey, Palágyi Kálmán, Hoffman Eric A, Sonka Milan
Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52240, USA.
IEEE Trans Med Imaging. 2005 Dec;24(12):1540-7. doi: 10.1109/TMI.2005.857653.
Matching of corresponding branchpoints between two human airway trees, as well as assigning anatomical names to the segments and branchpoints of the human airway tree, are of significant interest for clinical applications and physiological studies. In the past, these tasks were often performed manually due to the lack of automated algorithms that can tolerate false branches and anatomical variability typical for in vivo trees. In this paper, we present algorithms that perform both matching of branchpoints and anatomical labeling of in vivo trees without any human intervention and within a short computing time. No hand-pruning of false branches is required. The results from the automated methods show a high degree of accuracy when validated against reference data provided by human experts. 92.9% of the verifiable branchpoint matches found by the computer agree with experts' results. For anatomical labeling, 97.1% of the automatically assigned segment labels were found to be correct.
匹配两个人类气道树之间的对应分支点，以及为人类气道树的节段和分支点赋予解剖学名称，对于临床应用和生理学研究具有重要意义。过去，由于缺乏能够容忍体内树中典型的假分支和解剖变异的自动化算法，这些任务通常由人工执行。在本文中，我们提出了无需任何人工干预且在短计算时间内即可执行分支点匹配和体内树解剖学标记的算法。无需人工修剪假分支。当根据人类专家提供的参考数据进行验证时，自动化方法的结果显示出高度的准确性。计算机找到的可验证分支点匹配中有92.9%与专家结果一致。对于解剖学标记，发现自动分配的节段标签中有97.1%是正确的。
