https://scholars.lib.ntu.edu.tw/handle/123456789/607455
標題: | Improving algorithm for the alignment of consecutive, whole-slide, immunohistochemical section Images | 作者: | Liang C.-W RUEY-FENG CHANG Fang P.-W Chen C.-M. |
關鍵字: | Cell-level resolution;Image registration;Immunohistochemistry;Multidimensional graph-based registration;Proteome topology;Three-dimensional tissue reconstruction;Whole-slide images | 公開日期: | 2021 | 卷: | 12 | 期: | 1 | 來源出版物: | Journal of Pathology Informatics | 摘要: | Background: Accurate and precise alignment of histopathology tissue sections is a key step for the interpretation of the proteome topology and cell level three-dimensional (3D) reconstruction of diseased tissues. However, the realization of an automated and robust method for aligning nonglobally stained immunohistochemical (IHC) sections is still challenging. In this study, we aim to assess the feasibility of multidimensional graph-based image registration on aligning serial-section and whole-slide IHC section images. Materials and Methods: An automated, patch graph-based registration method was established and applied to align serial, whole-slide IHC sections at ×10 magnification (average 32,947 × 27,054 pixels). The alignment began with the initial alignment of high-resolution reference and translated images (object segmentation and rigid registration) and nonlinear registration of low-resolution reference and translated images, followed by the multidimensional graph-based image registration of the segmented patches, and finally, the fusion of deformed patches for inspection. The performance of the proposed method was formulated and evaluated by the Hausdorff distance between continuous image slices. Results: Sets of average 315 patches from five serial whole slide, IHC section images were tested using 21 different IHC antibodies across five different tissue types (skin, breast, stomach, prostate, and soft tissue). The proposed method was successfully automated to align most of the images. The average Hausdorff distance was 48.93 μm with a standard deviation of 14.94 μm, showing a significant improvement from the previously published patch-based nonlinear image registration method (average Hausdorff distance of 93.89 μm with 50.85 μm standard deviation). Conclusions: Our method was effective in aligning whole-slide tissue sections at the cell-level resolution. Further advancements in the screening of the proteome topology and 3D tissue reconstruction could be expected. ? 2021 Wolters Kluwer Medknow Publications. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114638908&doi=10.4103%2fjpi.jpi_106_20&partnerID=40&md5=1c1bd744d11744ed4d8733727db48577 https://scholars.lib.ntu.edu.tw/handle/123456789/607455 |
ISSN: | 22295089 | DOI: | 10.4103/jpi.jpi_106_20 |
顯示於: | 資訊工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。