论文标题
CT扫描中的多阶段和多个窗口框架的多阶段和多窗口框架
A multi view multi stage and multi window framework for pulmonary artery segmentation from CT scans
论文作者
论文摘要
这是Parse2022挑战最终结果中第9位的技术报告。我们通过使用基于3D CNN网络的两阶段方法来解决肺动脉的分割问题。粗模型用于定位ROI，并使用精细模型来完善分割结果。此外，为了提高细分性能，我们采用了多视图和多窗口级方法，同时我们采用了微调策略来减轻不一致的标签影响。
This is the technical report of the 9th place in the final result of PARSE2022 Challenge. We solve the segmentation problem of the pulmonary artery by using a two-stage method based on a 3D CNN network. The coarse model is used to locate the ROI, and the fine model is used to refine the segmentation result. In addition, in order to improve the segmentation performance, we adopt multi-view and multi-window level method, at the same time we employ a fine-tune strategy to mitigate the impact of inconsistent labeling.
