Yu Shuang, Tan Kok Kiong, Sng Ban Leong, Li Shengjin, Sia Alex Tiong Heng
National University of Singapore, Singapore.
National University of Singapore, Singapore.
Ultrasound Med Biol. 2014 Sep;40(9):1980-90. doi: 10.1016/j.ultrasmedbio.2014.03.010. Epub 2014 Jun 25.
Ultrasound imaging was used to detect the anatomic structure of lumbar spine from the transverse view, to facilitate needle insertion in epidural anesthesia. The interspinous images that represent proper needle insertion sites were identified automatically with image processing and pattern recognition techniques. On the basis of ultrasound video streams obtained in pregnant patients, the image processing and identification procedure in a previous work was tested and improved. The test results indicate that the pre-processing algorithm performs well on lumbar spine ultrasound images, whereas the classifier is not flexible enough for pregnant patients. To improve the accuracy of identification, we propose a cascading classifier that successfully located the proper needle insertion site on all of the 36 video streams collected from pregnant patients. The results indicate that the proposed image identification procedure is able to identify the ultrasound images of lumbar spine in an automatic manner, so as to facilitate the anesthetists' work to identify the needle insertion point precisely and effectively.
超声成像用于从横向视图检测腰椎的解剖结构，以利于硬膜外麻醉时的穿刺针插入。利用图像处理和模式识别技术自动识别代表合适穿刺针插入部位的棘突间图像。基于在孕妇身上获得的超声视频流，对先前工作中的图像处理和识别程序进行了测试和改进。测试结果表明，预处理算法在腰椎超声图像上表现良好，而分类器对孕妇来说不够灵活。为提高识别准确率，我们提出了一种级联分类器，该分类器成功地在从孕妇收集的所有36个视频流上定位了合适的穿刺针插入部位。结果表明，所提出的图像识别程序能够自动识别腰椎的超声图像，从而便于麻醉师精确有效地识别穿刺针插入点。
