We present an unsupervised blood cell segmentation algorithm for images taken from peripheral blood smear slides. Unlike prior algorithms the method is fast; fully automated; finds all objects---cells, cell groups and cell fragments---that do not intersect the image border; identifies the points interior to each object; finds an accurate one pixel wide border for each object; separates objects that just touch; and has been shown to work with a wide selection of red blood cell morphologies. The full algorithm was tested on two sets of images. In the first set of 47 images, 97.3% of the 2962 image objects were correctly segmented. The second test set---51 images from a different source---contained 5417 objects for which the success rate was 99.0%. The time taken for processing a 2272x1704 image ranged from 4.86 to 11.02 seconds on a Pentium 4, 2.4 GHz machine, depending on the number of objects in the image.
对于从外周血涂片上拍摄的图像,我们提出了一种无监督的血细胞分割算法。与现有算法不同,该方法快速。完全自动化;查找所有不与图像边界相交的对象-单元格,单元格组和单元格碎片-识别每个对象内部的点;为每个对象找到准确的一个像素宽的边框;分离仅接触的对象;并已显示可与多种红细胞形态一起使用。完整算法在两组图像上进行了测试。在第一组47张图像中,正确分割了2962个图像对象中的97.3%。第二个测试集-来自不同来源的51张图像-包含5417个对象,其成功率为99.0%。在奔腾4、2.4 GHz机器上处理2272x1704图像所需的时间在4.86到11.02秒之间,具体取决于图像中的对象数量。 P>
机译:使用各种颜色分割方法自动鉴定血液涂片光学显微镜图像中的红细胞
机译:通过可变倍率自动扫描通过自动扫描评价外周血白细胞鉴定的疗效
机译:来自人周围血液涂片图像的自动鉴定常规细胞
机译:外周血血液涂层图像中细胞的分割和边界鉴定
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机译:利用Curvelet变换提取外周血涂片图像中白细胞核候选区
机译:外围涂抹图像中白细胞分类的新分割和特征提取算法