IRIS-智能快速交互式分割法用于测量常染色体显性多囊肾病中的肝囊肿体积。
IRIS-Intelligent Rapid Interactive Segmentation for Measuring Liver Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease.
机构信息
Department of Radiology, MRI Research Institute, Weill Cornell Medicine, New York, NY 10065, USA.
出版信息
Tomography. 2022 Feb 9;8(1):447-456. doi: 10.3390/tomography8010037.
PURPOSE
To develop and integrate interactive features with automatic methods for accurate liver cyst segmentation in patients with autosomal dominant polycystic kidney and liver disease (ADPKD).
METHODS
SmartClick and antiSmartClick were developed using iterative region growth guided by spatial and intensity connections and were integrated with automated level set (LS) segmentation and graphical user interface, forming an intelligent rapid interactive segmentation (IRIS) tool. IRIS and LS segmentations of liver cysts on T2 weighted images of patients with ADPKD ( = 17) were compared with manual segmentation as ground truth (GT).
RESULTS
Compared to manual GT, IRIS reduced the segmentation time by more than 10-fold. Compared to automated LS, IRIS reduced the mean liver cyst volume error from 42.22% to 13.44% ( < 0.001). IRIS segmentation agreed well with manual GT (79% dice score and 99% intraclass correlation coefficient).
CONCLUSION
IRIS is feasible for fast, accurate liver cyst segmentation in patients with ADPKD.
目的
为常染色体显性多囊肾病和肝病（ADPKD）患者的肝囊肿自动分割开发并集成交互功能。
方法
利用空间和强度连接引导的迭代区域生长开发了 SmartClick 和 antiSmartClick，并与自动化水平集（LS）分割和图形用户界面集成，形成了智能快速交互分割（IRIS）工具。将 17 例 ADPKD 患者 T2 加权图像上的肝囊肿的 IRIS 和 LS 分割与手动分割作为金标准（GT）进行比较。
结果
与手动 GT 相比，IRIS 将分割时间缩短了 10 多倍。与自动 LS 相比，IRIS 将肝囊肿体积误差的平均值从 42.22%降低到 13.44%（<0.001）。IRIS 分割与手动 GT 吻合较好（Dice 评分 79%，组内相关系数 99%）。
结论
IRIS 可用于 ADPKD 患者肝囊肿的快速、准确分割。
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