Reconstruction of vessel structures from serial whole slide sections of murine liver samples

Michael Schwier; Horst Karl Hahn; Uta Dahmen; Olaf Dirsch

doi:10.1117/12.2008112

29 March 2013 Reconstruction of vessel structures from serial whole slide sections of murine liver samples

Michael Schwier, Horst Karl Hahn, Uta Dahmen, Olaf Dirsch

Author Affiliations +

Proceedings Volume 8676, Medical Imaging 2013: Digital Pathology; 86760D (2013) https://doi.org/10.1117/12.2008112
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Image-based analysis of the vascular structures of murine liver samples is an important tool for scientists to understand liver physiology and morphology. Typical assessment methods are MicroCT, which allows for acquiring images of the whole organ while lacking resolution for fine details, and confocal laser scanning microscopy, which allows detailed insights into fine structures while lacking the broader context. Imaging of histological serial whole slide sections is a recent technology able to fill this gap, since it provides a fine resolution up to the cellular level, but on a whole organ scale. However, whole slide imaging is a modality providing only 2D images. Therefore the challenge is to use stacks of serial sections from which to reconstruct the 3D vessel structures. In this paper we present a semi-automatic procedure to achieve this goal. We employ an automatic method that detects vessel structures based on continuity and shape characteristics. Furthermore it supports the user to perform manual corrections where required. With our methods we were able to successfully extract and reconstruct vessel structures from a stack of 100 and a stack of 397 serial sections of a mouse liver lobe, thus proving the potential of our approach.

Citation Download Citation

Michael Schwier, Horst Karl Hahn, Uta Dahmen, and Olaf Dirsch "Reconstruction of vessel structures from serial whole slide sections of murine liver samples", Proc. SPIE 8676, Medical Imaging 2013: Digital Pathology, 86760D (29 March 2013); https://doi.org/10.1117/12.2008112

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