ArticleResearch and practice in thrombosis and haemostasis2026
High-throughput Image-based Matrix Analysis Platform Software: development of an algorithm for standardized characterization of high-resolution fibrin clot images.
Article in Research and practice in thrombosis and haemostasis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Scanning electron microscopy has been gaining traction as a tool to provide high-resolution images of biological specimens such as blood clots to associate their properties with clinical outcomes. However, there lacks a "gold-standard" method of quantifying these images. Objective: To develop and validate a novel high-throughput, semiautomated computational pipeline for quantifying high-resolution images of biological samples called HIMAPS (High-throughput Image-based Matrix Analysis Platform Software). Methods: From an imported image, a region of interest is defined, and individual pixels are calibrated to physical dimensions (μm). The brightness intensity values of each pixel are then normalized to generate relative intensity values and are subjected to the stratification algorithm to partition the image into layers. The identified fiber structures are enhanced and visualization is optimized as binary masks undergo morphologic refinement to reduce noise, which can then be quantified for: (1) fiber thickness from a skeletonized representation of the network, and (2) network porosity and density from identification of pores. Results: Fiber thickness was used as a validation method by comparing against the published standardization manual protocol. Our algorithm was within the 95% CI of the manual measurements ( Conclusion: This algorithm can accurately quantify physical properties of clots such as fiber thickness, fiber matrix density, and porosity in a semiautomated, rapid, and unbiased manner.
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