Paper Info
Title
A framework for 3D vessel analysis using whole slide images of liver tissue sections.
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.
Year
Venue
Keywords
2016
International journal of computational biology and drug design
3D Vessel Structure,Digital Pathology,Liver Pathology,Pathology Image Analysis,Whole Slide Imaging
Field
DocType
Volume
Structure analysis,Computer vision,Volume rendering,Segmentation,Computer science,Interpolation,Spatial relationship,Image segmentation,Digital pathology,Artificial intelligence,Image registration
Journal
9
Issue
Citations 
PageRank 
1/2
2
0.37
References 
Authors
0
8
Name
Order
Citations
PageRank
Yanhui Liang1166.50
Fusheng Wang2173.14
Darren Treanor312113.20
Derek R. Magee436335.94
nicholas roberts522.40
George Teodoro615022.18
Yangyang Zhu771.24
Jun Kong810617.74