Draper K J, Blake C C, Gowman L, Downey D B, Fenster A
Department of Medical Biophysics, The University of Western Ontario, London, Canada.
Med Phys. 2000 Aug;27(8):1971-9. doi: 10.1118/1.1287437.
An algorithm was developed in order to reduce operator dependence in ultrasound-guided breast biopsy, by automatically locating the needle in the ultrasound image, and displaying its location on the image for the user. Ultrasound images of a typical breast biopsy needle inserted in a tissue-mimicking agar were obtained to test the algorithm. The resulting images were examined by a group of observers who recorded the values of the angle, intercept and tip coordinates of the needle in the image, and inter- and intra-observer variability studies were performed on the results. The results of the algorithm segmentation were compared to the values recorded by the observers, and physical measurements recorded at the time the images were acquired. The algorithm segmentation was precise enough to successfully (when considering angle and tip segmentation) target 90% of tumors of 4.5 mm in diameter situated at the center of the image.
为了减少超声引导下乳腺活检对操作人员的依赖,开发了一种算法,该算法可自动在超声图像中定位针头,并为用户在图像上显示其位置。获取了插入模拟组织琼脂中的典型乳腺活检针的超声图像,以测试该算法。一组观察者检查了所得图像,他们记录了图像中针头的角度、截距和尖端坐标值,并对结果进行了观察者间和观察者内的变异性研究。将算法分割的结果与观察者记录的值以及图像采集时记录的物理测量值进行了比较。该算法分割足够精确,能够成功(在考虑角度和尖端分割时)定位位于图像中心的90%直径为4.5毫米的肿瘤。