使用COMPASS在CT尿路造影（CTU）中进行输尿管追踪和分割。

Ureter tracking and segmentation in CT urography (CTU) using COMPASS.

作者信息

Hadjiiski Lubomir, Zick David, Chan Heang-Ping, Cohan Richard H, Caoili Elaine M, Cha Kenny, Zhou Chuan, Wei Jun

机构信息

Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109-5842.

出版信息

Med Phys. 2014 Dec;41(12):121906. doi: 10.1118/1.4901412.

DOI:10.1118/1.4901412

PMID:25471966

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4240782/

Abstract

PURPOSE

The authors are developing a computerized system for automated segmentation of ureters in CTU, referred to as combined model-guided path-finding analysis and segmentation system (COMPASS). Ureter segmentation is a critical component for computer-aided diagnosis of ureter cancer.

METHODS

COMPASS consists of three stages: (1) rule-based adaptive thresholding and region growing, (2) path-finding and propagation, and (3) edge profile extraction and feature analysis. With institutional review board approval, 79 CTU scans performed with intravenous (IV) contrast material enhancement were collected retrospectively from 79 patient files. One hundred twenty-four ureters were selected from the 79 CTU volumes. On average, the ureters spanned 283 computed tomography slices (range: 116-399, median: 301). More than half of the ureters contained malignant or benign lesions and some had ureter wall thickening due to malignancy. A starting point for each of the 124 ureters was identified manually to initialize the tracking by COMPASS. In addition, the centerline of each ureter was manually marked and used as reference standard for evaluation of tracking performance. The performance of COMPASS was quantitatively assessed by estimating the percentage of the length that was successfully tracked and segmented for each ureter and by estimating the average distance and the average maximum distance between the computer and the manually tracked centerlines.

RESULTS

Of the 124 ureters, 120 (97%) were segmented completely (100%), 121 (98%) were segmented through at least 70%, and 123 (99%) were segmented through at least 50% of its length. In comparison, using our previous method, 85 (69%) ureters were segmented completely (100%), 100 (81%) were segmented through at least 70%, and 107 (86%) were segmented at least 50% of its length. With COMPASS, the average distance between the computer and the manually generated centerlines is 0.54 mm, and the average maximum distance is 2.02 mm. With our previous method, the average distance between the centerlines was 0.80 mm, and the average maximum distance was 3.38 mm. The improvements in the ureteral tracking length and both distance measures were statistically significant (p < 0.0001).

CONCLUSIONS

COMPASS improved significantly the ureter tracking, including regions across ureter lesions, wall thickening, and the narrowing of the lumen.

摘要

目的

作者正在开发一种用于CTU中输尿管自动分割的计算机系统，称为联合模型引导路径查找分析与分割系统（COMPASS）。输尿管分割是输尿管癌计算机辅助诊断的关键组成部分。

方法

COMPASS由三个阶段组成：（1）基于规则的自适应阈值处理和区域生长，（2）路径查找和传播，以及（3）边缘轮廓提取和特征分析。经机构审查委员会批准，从79份患者病历中回顾性收集了79例经静脉（IV）造影剂增强的CTU扫描图像。从79个CTU容积中选取了124条输尿管。平均而言，输尿管跨越283层计算机断层扫描切片（范围：116 - 399，中位数：301）。超过一半的输尿管包含恶性或良性病变，有些因恶性肿瘤导致输尿管壁增厚。通过手动确定124条输尿管中每条的起始点，以初始化COMPASS的跟踪。此外，手动标记每条输尿管的中心线，并将其用作评估跟踪性能的参考标准。通过估计每条输尿管成功跟踪和分割的长度百分比，以及估计计算机跟踪中心线与手动跟踪中心线之间的平均距离和平均最大距离，对COMPASS的性能进行定量评估。

结果

在124条输尿管中，120条（97%）被完全分割（100%），121条（98%）被分割至少70%，123条（99%）被分割至少其长度的50%。相比之下，使用我们之前的方法，85条（69%）输尿管被完全分割（100%），100条（81%）被分割至少70%，107条（86%）被分割至少其长度的50%。使用COMPASS时，计算机跟踪中心线与手动生成的中心线之间的平均距离为0.54毫米，平均最大距离为2.02毫米。使用我们之前的方法时，中心线之间的平均距离为0.80毫米，平均最大距离为3.38毫米。输尿管跟踪长度以及两种距离测量方法的改进具有统计学意义（p < 0.0001）。