A framework for 3D vessel analysis using whole slide images of liver tissue sections. (2016)

• Record Type: Journal Article
• Authors: Liang, Yanhui; Wang, Fusheng; Treanor, Darren; Magee, Derek; Roberts, Nick; Teodoro, George; Zhu, Yangyang; Kong, Jun
• Is Part Of: International journal of computational biology and drug design. Volume 9:Number 1/2(2016)
• Page Start: 102
• Page End: 119
• Publication Date: 2016
• Subjects: whole slide imaging -- digital pathology -- pathology image analysis -- 3D vessel structure -- liver pathology -- liver tissue sections -- 3D images -- image registration -- image segmentation -- vessel cross-section association -- interpolation -- volumetric rendering -- similarity function -- constrained integer programming; Computational biology -- Periodicals; Drugs -- Design -- Periodicals; 570.285
• Languages: English
• ISSNs: 1756-0756

Abstract

Three-dimensional (3D) high resolution microscopic images have high potential for improving the understanding of both normal and disease processes where structural changes or spatial relationship of disease features are significant. In this paper, we develop a complete framework applicable to 3D pathology analytical imaging, with an application to whole slide images of sequential liver slices for 3D vessel structure analysis. The analysis workflow consists of image registration, segmentation, vessel cross-section association, interpolation, and volumetric rendering. To identify biologically-meaningful correspondence across adjacent slides, we formulate a similarity function for four association cases. The optimal solution is then obtained by constrained integer programming. We quantitatively and qualitatively compare our vessel reconstruction results with human annotations. Validation results indicate a satisfactory concordance as measured both by region-based and distance-based metrics. These results demonstrate a promising 3D vessel analysis framework for whole slide images of liver tissue sections.