一种用于3D逐切片多染色肾脏病理配准的端到端流程
An End-to-end Pipeline for 3D Slide-wise Multi-stain Renal Pathology Registration
AI总结：
本文提出一种用于穿刺活检连续切片多染色WSI的端到端3D逐切片配准Docker流程，验证了Map3D方法在多染色和穿刺活检样本上的适用性。
摘要：
在连续切片全切片图像（WSIs）上进行3D环境下的组织检查和定量分析是一项费时费力的工作。我们之前的研究提出了一种新颖的基于配准的方法（Map3D），可将WSIs自动对齐到相同的物理空间，从而减少了从WSIs中筛查连续切片的人力。然而，我们Map3D方法的配准性能仅在大规模肾脏组织样本的单染色WSIs上进行了评估。在本文中，我们提供了一个Docker，用于在多染色模式下对穿刺活检连续切片进行端到端3D逐切片配准流程。本研究的贡献有三方面：（1）我们发布了一个用于端到端多染色WSI配准的容器化Docker。（2）我们证明Map3D流程能够从多染色WSI进行切片配准。（3）我们验证Map3D流程也可应用于穿刺活检组织样本。源代码和Docker已在https://github.com/hrlblab/Map3D上公开提供。
英文摘要：
Tissue examination and quantification in a 3D context on serial section whole slide images (WSIs) were laborintensive and time-consuming tasks. Our previous study proposed a novel registration-based method (Map3D) to automatically align WSIs to the same physical space, reducing the human efforts of screening serial sections from WSIs. However, the registration performance of our Map3D method was only evaluated on single-stain WSIs with large-scale kidney tissue samples. In this paper, we provide a Docker for an end-to-end 3D slide-wise registration pipeline on needle biopsy serial sections in a multi-stain paradigm. The contribution of this study is three-fold: (1) We release a containerized Docker for an end-to-end multi-stain WSI registration. (2) We prove that the Map3D pipeline is capable of sectional registration from multi-stain WSI. (3) We verify that the Map3D pipeline can also be applied to needle biopsy tissue samples. The source code and the Docker have been made publicly available at https://github.com/hrlblab/Map3D.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
