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Co-registration tool for Large format whole mount prostate multi-plex histology

机译:用于大型格式的共同登记工具全山前列腺多重Plex组织学

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Purpose: Multiplex staining allows molecular co-localization analysis of same cell or tissue sections and maximizes the amount of data acquired from individual samples. We developed a non-linear registration framework for automated alignment of whole mount multiplexed histology images of prostate cancer. To achieve a precise automatic fit of bleached and restained high resolution tissue samples, a patch-based approach is proposed to improve annotation speed and analysis. Methods: The three-step co-registration process begins with a coarse low-resolution registration of the IHC stained image to the fixed H&E-stained image. The initial registration is then refined separately for each high-resolution patch using a smaller search window. Finally, registered patches are stitched back together using speeded up robust features (SURF). We apply the method to five multiplex whole mount prostate histology slides. To determine its effectiveness, we compare the automatic registration to the initial coarse registration and a manual control point based-method varying the number of control points. Results: For the control point-based approach, 25, 50, and 100 manually placed set landmarks resulted in a decrease of-76.20%, -75.9% and -75.48% of the root mean squared error (RMSE), respectively. Compared to the initial registration an improvement of-76.29% of RMSE can be seen, illustrating the potential benefits of a patch-based automatic approach. Conclusion: The proposed method achieved excellent registration of the IHC to the input image. The automated method for registration of multiplexed histology images achieves high accuracy in shorter time and with greater reproducibility than conventional registration approaches and semi-automatic control points without the need for time consuming and subjective manual control-point setting. The accuracy of the fit especially improves in complex areas close to tissue tears and folds.
机译:目的:多重染色允许的相同细胞或组织切片的分子共定位分析和最大化从单个样品获得的数据的量。我们开发了用于前列腺癌的整个安装多路复用组织学图像的自动校准的非线性注册框架。为了实现漂白和复染高分辨率组织样品的精确自动配合,基于块拼贴的方法,提出了以提高注释速度和分析。方法:三步共配准过程开始于IHC的粗低分辨率登记染色图像到固定H&E染色的图像。初始登记然后用于使用较小的搜索窗口中的每个高分辨率补丁分别细化。最后,注册补丁缝合到一起使用加速稳健特征(SURF)。我们采用该方法五张多重整装前列腺组织学幻灯片。以确定其有效性,我们自动注册比较初始粗配准和手动控制点为基础的方法不同的控制点的数目。结果:对于控制基于点的方法,25,50,和100个手动放置地标集合分别导致的-76.20%,-75.9%和均方根误差(RMSE)的-75.48%的减少,。与初始登记的-76.29 RMSE的%的改进中可以看出,示出了基于块拼贴的自动方法的潜在益处。结论:所提出的方法实现的IHC的优良登记到输入图像。用于多路复用的组织学图像的配准的自动方法在更短的时间,并用比常规登记更大的再现方法和半自动的控制点,而无需耗时和主观手动控制点设定实现高的精度。拟合的精度提高尤其是在复杂的地区接近组织撕裂和褶皱。

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