What is it about?

This program detects molecules with great accuracy from microscopy images. This also enables to track particles/molecules from various successive images, i.e. it enables particle tracking in time sequence images. one can automatically get particle heights, volumes and areas of molecules.

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Why is it important?

Vital to the analysis of biomolecules in microscopy imagery is the initial detection of individual particles from large-scale images. Threshold and watershed algorithms are conventional for automatic particle detection but demand manual image preprocessing and produce particle boundaries which deform as a function of user-defined parameters, producing imprecise results subject to bias. Here, we introduce the Hessian blob to address these shortcomings. Combining a scale-space framework with measures of local image curvature, the Hessian blob formally defines particle centers and their boundaries, both to subpixel precision. Resulting particle boundaries are independent of user defined parameters, with no image preprocessing required. We demonstrate through direct comparison that the Hessian blob algorithm more accurately detects biomolecules than conventional microscopy particle detection techniques.

Perspectives

This algorithm proves largely insensitive to common imaging artifacts and noise, delivering a stable framework for particle analysis in microscopy

Nagaraju Chada
Johns Hopkins University

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This page is a summary of: The Hessian Blob Algorithm: Precise Particle Detection in Atomic Force Microscopy Imagery, Scientific Reports, January 2018, Springer Science + Business Media,
DOI: 10.1038/s41598-018-19379-x.
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