Sheng Chen, Li Li, Pei Wang
College of Information, Shanghai Normal University, Shanghai, People's Republic of China.
Int J Med Robot. 2009 Sep;5(3):332-40. doi: 10.1002/rcs.265.
This paper presents a computer-aided method for automatic detection of the positioning of endotracheal, feeding and nasogastric tubes, and the identification of tube types in radiography for intensive care unit (ICU) patients. Application of this method may allow clinicians to detect the tube tips more easily and accurately, and thus improve the quality of patient care in the ICU.
One-hundred-and-seven portable X-ray images were collected from 20 patients, using a Kodak computed radiography system. It was determined whether each image did or did not have a tube and which kind of tube was present. In order to evaluate the performance of the proposed tube detection method, an experienced chest radiologist reviewed all images from the 20 patients and provided the true position of these tubes. The automatic detection results could then be compared with the actual results to determine the success rate.
Preliminary results show that the computer-aided technique has a detection rate of 94% for endotracheal tubes, with 0.6 false positives per image, and 82% for both feeding and nasogastric tubes, with 0.4 and 0.5 false positives per image, respectively.
The novel detection technique can accurately detect the tubes in ICU chest radiographs at a high sensitivity level with an acceptable false positive rate.
本文介绍了一种计算机辅助方法,用于自动检测重症监护病房(ICU)患者胸部X光片中气管内插管、饲管和鼻胃管的位置,并识别管型。应用该方法可使临床医生更轻松、准确地检测管端,从而提高ICU患者的护理质量。
使用柯达计算机放射成像系统,从20名患者收集了107张便携式X光图像。确定每张图像是否有插管以及存在哪种类型的插管。为评估所提出的插管检测方法的性能,一名经验丰富的胸部放射科医生查看了这20名患者的所有图像,并给出这些插管的真实位置。然后将自动检测结果与实际结果进行比较,以确定成功率。
初步结果显示,计算机辅助技术对气管内插管的检测率为94%,每张图像的假阳性为0.6,对饲管和鼻胃管的检测率均为82%,每张图像的假阳性分别为0.4和0.5。
这种新型检测技术能够以高灵敏度、可接受的假阳性率准确检测ICU胸部X光片中的插管。