骨盆CT扫描出血分割的混合方法

Pavani Davuluri, Jie Wu, Ashwin Belle, Charles Cockrell, Yang Tang, Kevin Ward, K. Najarian, R. H. Hargraves
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引用次数: 2

摘要

出血是严重骨盆骨折患者在受伤后24小时内死亡的主要原因。因此,对医生来说,快速识别出血和评估出血严重程度是至关重要的。然而,医生对所有CT图像进行评估是相当耗时的。因此,需要一个自动出血分割系统来辅助医生。本文提出了一种骨盆CT扫描出血分割的混合方法。该方法利用区域增长技术,整合了前后切片的对比度信息。结果表明,该方法能较好地分割出血,效果良好。同时测定出血量。采用统计t检验来确定采用所提出的方法计算的出血量是否与人工检测的出血量有显著差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid approach for hemorrhage segmentation in pelvic CT scans
Hemorrhage is the leading cause of death in patients with severe pelvic fractures within the first 24 hours after the injury. Hence, it is vital for physicians to quickly identify hemorrhage and assess bleeding severity. However, it is rather time consuming for physicians to evaluate all the CT images. Therefore, an automated hemorrhage segmentation system is needed to assist physicians. This paper proposes a hybrid approach for hemorrhage segmentation from pelvic CT scans. This approach utilizes region growing technique with integration of contrast information from the previous and subsequent slices. The results show that the method is able to segment hemorrhage well with acceptable results. Hemorrhage volume is also determined. A statistical t-test is conducted to determine if the calculated hemorrhage volume using the proposed method is significantly different from the manually detected volume.
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