Segmentation and modeling of large-scale microvascular networks: a survey
Year: 2025
Type: review
Abstract: Recent advances in three-dimensional microscopy enable imaging of whole-organ microvascular networks in small animals. Since microvasculature plays a crucial role in tissue development and function, its structure may provide diagnostic biomarkers and insight into disease progression. However, the microscopy community currently lacks benchmarks for scalable algorithms to measure these potential biomarkers. While many algorithms exist for segmenting vessel-like structures and extracting their surface features and connectivity, they have not been thoroughly evaluated on modern gigavoxel-scale images. In this paper, we propose a comprehensive yet compact survey of available algorithms. We focus on essential features for microvascular analysis, including extracting vessel surfaces and the network's associated connectivity. We select a series of algorithms based on popularity and availability and provide a thorough quantitative analysis of their performance on datasets acquired using light sheet fluorescence microscopy (LSFM), knife-edge scanning microscopy (KESM), and X-ray microtomography (µ-CT).
Source: Frontiers in Bioinformatics
Authors: Helya Goharbavang, Artem T. Ashitkov, Athira Pillai, Joshua D. Wythe, Guoning Chen, David Mayerich
Institutions: University of Houston, University of Virginia
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,077
Awards: Structural and Molecular Phenotyping of Embryonic Development through Multi-Modal Optical Imaging, Decoding the Molecular and Cellular Mechanisms of Mutant KRAS-driven Brain Arteriovenous Malformations, Improving the Accuracy of Lupus Nephritis Diagnosis using Biomarkers Derived from Ultraviolet and Mid-infrared Spectroscopic Imaging, Early detection of treatment response in myelofibrosis by polarization-sensitive mid-infrared spectroscopic imaging
OpenAlex ID: W4415729842