Liver Whole Slide Image Analysis for 3D Vessel Reconstruction

• Type of Material: Article
• Authors: Yanhui Liang, Emory University; Fusheng Wang, Emory University; Darren Treanor, Leeds Institute of Molecular Medicine; Derek Magee, University of Leeds; George Teodoro, University of Brasilia; Yangyang Zhu, Emory University; Jun Kong, Emory University
• Language: English
• Date: 2015-01-01
• Publisher: IEEE
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2015 IEEE.
• Final Published Version (URL): http://dx.doi.org/10.1109/ISBI.2015.7163845
• Title of Journal or Parent Work: 2015 IEEE 12TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI)
• Volume: 2015-July
• Start Page: 182
• End Page: 185
• Grant/Funding Information: This research is supported in part by grants from National Institute of Health K25CA181503, National Science Foundation ACI 1443054 and IIS 1350885, and CNPq.
• Keywords: Whole Slide Image Analysis; Digital Pathology; 3D Vessel Analysis; Technology; Science & Technology; Engineering, Biomedical; Engineering, Electrical & Electronic; Vessel Reconstruction; Radiology, Nuclear Medicine & Medical Imaging; Life Sciences & Biomedicine; Engineering
• Research Categories: Health Sciences, Radiology; Engineering, Biomedical

Abstract

The emergence of digital pathology has enabled numerous quantitative analyses of histopathology structures. However, most pathology image analyses are limited to two-dimensional datasets, resulting in substantial information loss and incomplete interpretation. To address this, we have developed a complete framework for three-dimensional whole slide image analysis and demonstrated its efficacy on 3D vessel structure analysis with liver tissue sections. The proposed workflow includes components on image registration, vessel segmentation, vessel cross-section association, object interpolation, and volumetric rendering. For 3D vessel reconstruction, a cost function is formulated based on shape descriptors, spatial similarity and trajectory smoothness by taking into account four vessel association scenarios. An efficient entropy-based Relaxed Integer Programming (eRIP) method is proposed to identify the optimal inter-frame vessel associations. The reconstructed 3D vessels are both quantitatively and qualitatively validated. Evaluation results demonstrate high efficiency and accuracy of the proposed method, suggesting its promise to support further 3D vessel analysis with whole slide images.