Multi-stained whole slide image alignment in digital pathology
Multi-stained whole slide image alignment in digital pathology
复制标题
数字病理学中的多染色全幻灯片图像对齐
DOI：
10.1117/12.2082256
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Gloria Bueno García
中科院分区：
文献类型：
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作者：
O. Déniz;David Toomey;C. Conway;Gloria Bueno García
在数字病理学中，最简单但最有用的功能之一是能够在计算机显示器上同时查看组织的连续切片。这使得病理学家能够在一次检查中评估患者的组织学和多种标记物的表达。然而，此过程中的速率限制步骤是病理学家打开每个单独的图像、在查看器内对齐切片（一次最多四张幻灯片）、然后手动在切片周围移动所需的时间。此外，由于组织处理和预分析步骤，具有不同染色的切片在两次采集之间具有非线性变化，也就是说，它们会在切片之间拉伸并改变形状。迄今为止，还没有任何解决方案能够接近将连续部分自动对齐到一张合成图像中的可行解决方案。这项研究工作解决了这个问题，获得了一种自动串行切片对齐工具，使病理学家能够在单个查看器中简单地滚动浏览各个切片。为此，使用了一种基于多分辨率强度的配准方法，该方法使用互信息作为相似性度量，并使用了基于进化过程和双线性变换的优化器。为了表征该算法的性能，考虑了用苏木精-伊红 (HE)、雌激素受体 (ER)、孕激素受体 (PR)、Ki67 和人表皮生长因子受体 2 (Her2) 染色的 40 个病例 x 5 个不同的连续切片。获得的定性结果很有希望，运行解释代码的高达 14660x5799 图像的平均计算时间为 26.4 秒。
In Digital Pathology, one of the most simple and yet most useful feature is the ability to view serial sections of tissue simultaneously on a computer monitor. This enables the pathologist to evaluate the histology and expression of multiple markers for a patient in a single review. However, the rate limiting step in this process is the time taken for the pathologist to open each individual image, align the sections within the viewer, with a maximum of four slides at a time, and then manually move around the section. In addition, due to tissue processing and pre-analytical steps, sections with different stains have non-linear variations between the two acquisitions, that is, they will stretch and change shape from section to section. To date, no solution has come close to a workable solution to automatically align the serial sections into one composite image. This research work address this problem to obtain an automated serial section alignment tool enabling the pathologists to simply scroll through the various sections in a single viewer. To this aim a multi-resolution intensity-based registration method using mutual information as a similarity metric, an optimizer based on an evolutionary process and a bilinear transformation has been used. To characterize the performance of the algorithm 40 cases x 5 different serial sections stained with hematoxiline-eosine (HE), estrogen receptor (ER), progesterone receptor (PR), Ki67 and human epidermal growth factor receptor 2 (Her2), have been considered. The qualitative results obtained are promising, with average computation time of 26.4s for up to 14660x5799 images running interpreted code.