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.
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:外周血涂片玻片图像中细胞的分割和边界鉴定
机译:从注射B16-BL6黑色素瘤细胞的小鼠外周血中分离出的白细胞中的诊断生物标志物的微阵列鉴定。
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