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Automatic segmentation of histological structures in normal and neoplastic mammary gland tissue sections

机译:正常和肿瘤乳腺组织切片中组织学结构的自动分割

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In this paper we present a scheme for real time segmentation of histological structures in microscopic images of normal and neoplastic mammary gland sections. Paraffin embedded or frozen tissue blocks are sliced, and sections are stained with hematoxylin and eosin (H&E). The sections are then imaged using conventional bright field microscopy. The background of the images is corrected by arithmetic manipulation using a "phantom". Then we use the fast marching method with a speed function that depends on the brightness gradient of the imageto obtain a preliminary approximation to the boundaries of the structures of interest within a region of interest (ROI) of the entire section manually selected b the user. We use the result of the fast marching method as the initial condition for the level set motion equation. We run this last method for a few steps and obtain the final result of the segmentation. These results can be connected from section to section to build a three-dimensional reconstruction of the entire tissue block that we are stud ing.
机译:本文介绍了正常和肿瘤乳腺部分微观图像中的组织学结构实时分割的方案。切片嵌入或冷冻组织块切片,并且用苏木精和曙红(H&E)染色。然后使用传统的明场显微镜进行成像部分。通过使用“幻像”通过算术操纵来校正图像的背景。然后,我们使用快速行进方法具有速度函数,该速度函数取决于Imageto的亮度梯度,获得对手动选择的整个部分的感兴趣区域内的感兴趣区域内的初步近似的初步近似值(ROI)。我们使用快速行进方法的结果作为级别设定运动方程的初始条件。我们运行最后一个方法几步并获得分段的最终结果。这些结果可以从部分到部分连接,以构建我们螺叠的整个组织块的三维重建。

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