A 3D Primary Vessel Reconstruction Framework with Serial Microscopy Images
Three dimensional microscopy images present significant potential to enhance biomedical studies. This paper presents an automated method for quantitative analysis of 3D primary vessel structures with histology whole slide images. With registered microscop
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Emory University, Atlanta, GA, USA Stony Brook University, Stony Brook, NY, USA Leeds Teaching Hospitals NHS Trust, Leeds, UK 4 The University of Leeds, Leeds, UK 5 University of Bras´ılia, Bras´ılia, DF, Brazil
Abstract. Three dimensional microscopy images present significant potential to enhance biomedical studies. This paper presents an automated method for quantitative analysis of 3D primary vessel structures with histology whole slide images. With registered microscopy images of liver tissue, we identify primary vessels with an improved variational level set framework at each 2D slide. We propose a Vessel Directed Fitting Energy (VDFE) to provide prior information on vessel wall probability in an energy minimization paradigm. We find the optimal vessel cross-section associations along the image sequence with a two-stage procedure. Vessel mappings are first found between each pair of adjacent slides with a similarity function for four association cases. These bi-slide vessel components are further linked by Bayesian Maximum A Posteriori (MAP) estimation where the posterior probability is modeled as a Markov chain. The efficacy of the proposed method is demonstrated with 54 whole slide microscopy images of sequential sections from a human liver.
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Introduction
Whole slide histological images contain rich information about morphological and pathological characteristics of biological systems, enabling researchers and clinicians to gain insights on the underlying mechanisms of the disease onsets and pathological evolutions of distinct cancers. Although numerous imaging analytical approaches have been proposed to quantitatively analyze the 2D biological structures (such as nuclei and vessels) in microscopy images [1], various clinical applications require 3D modeling of the micro-anatomic objects for better characterization of their biological structures in practice. One such application is liver disease where clinicians and researchers are interested in the 3D structural features of primary vessels from a sequence of 2D images of adjacent liver
This research was supported in part by National Institute of Health K25CA181503, National Science Foundation ACI 1443054 and IIS 1350885, and CNPq.
c Springer International Publishing Switzerland 2015 N. Navab et al. (Eds.): MICCAI 2015, Part III, LNCS 9351, pp. 251–259, 2015. DOI: 10.1007/978-3-319-24574-4_30
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sections [2,3], as illustrated in Fig. 1(a). Although there are a large suite of methods for vessel structure analysis, they mainly focus on radiology image analysis and are not directly applicable to high resolution whole slide histological images encoding enormous information of complex structures at cellular level. In this paper, we propose an automated framework for 3D primary vessel reconstruction with a set of registered histological whole slide images of liver sequential tissue sections. To identify vessels, we use an improved variational level set method with a Vessel Directed Fitting Energy (VDFE) as prior information of vesse
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