Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland.
Bioinformatics. 2018 Sep 1;34(17):3013-3021. doi: 10.1093/bioinformatics/bty210.
Digital pathology enables new approaches that expand beyond storage, visualization or analysis of histological samples in digital format. One novel opportunity is 3D histology, where a three-dimensional reconstruction of the sample is formed computationally based on serial tissue sections. This allows examining tissue architecture in 3D, for example, for diagnostic purposes. Importantly, 3D histology enables joint mapping of cellular morphology with spatially resolved omics data in the true 3D context of the tissue at microscopic resolution. Several algorithms have been proposed for the reconstruction task, but a quantitative comparison of their accuracy is lacking.
We developed a benchmarking framework to evaluate the accuracy of several free and commercial 3D reconstruction methods using two whole slide image datasets. The results provide a solid basis for further development and application of 3D histology algorithms and indicate that methods capable of compensating for local tissue deformation are superior to simpler approaches.
Code: https://github.com/BioimageInformaticsTampere/RegBenchmark. Whole slide image datasets: http://urn.fi/urn: nbn: fi: csc-kata20170705131652639702.
Supplementary data are available at Bioinformatics online.
数字病理学能够实现新的方法，超越数字格式的组织样本存储、可视化或分析。一个新颖的机会是三维组织学，其中根据组织切片的序列进行计算形成样本的三维重建。这允许在三维空间中检查组织架构，例如用于诊断目的。重要的是，三维组织学能够在组织的真实三维环境中，以微观分辨率联合映射细胞形态与空间分辨的组学数据。已经提出了几种用于重建任务的算法，但缺乏对其准确性的定量比较。
我们开发了一个基准测试框架，使用两个全幻灯片图像数据集来评估几种免费和商业 3D 重建方法的准确性。结果为进一步开发和应用三维组织学算法提供了坚实的基础，并表明能够补偿局部组织变形的方法优于更简单的方法。
代码：https://github.com/BioimageInformaticsTampere/RegBenchmark。全幻灯片图像数据集：http://urn.fi/urn: nbn: fi: csc-kata20170705131652639702。
补充数据可在 Bioinformatics 在线获得。
