Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging

Scientific Reports
Eldad Afik

Abstract

Three-dimensional particle tracking is an essential tool in studying dynamics under the microscope, namely, fluid dynamics in microfluidic devices, bacteria taxis, cellular trafficking. The 3d position can be determined using 2d imaging alone by measuring the diffraction rings generated by an out-of-focus fluorescent particle, imaged on a single camera. Here I present a ring detection algorithm exhibiting a high detection rate, which is robust to the challenges arising from ring occlusion, inclusions and overlaps, and allows resolving particles even when near to each other. It is capable of real time analysis thanks to its high performance and low memory footprint. The proposed algorithm, an offspring of the circle Hough transform, addresses the need to efficiently trace the trajectories of many particles concurrently, when their number in not necessarily fixed, by solving a classification problem, and overcomes the challenges of finding local maxima in the complex parameter space which results from ring clusters and noise. Several algorithmic concepts introduced here can be advantageous in other cases, particularly when dealing with noisy and sparse data. The implementation is based on open-source and cross-platform software p...Continue Reading

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Citations

Sep 9, 2017·Nature Communications·Eldad Afik, Victor Steinberg

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Methods Mentioned

BETA
fluorescence microscopy

Software Mentioned

Numpy
EDCircles
Python
OpenCV
Ubuntu linux
Octave splines
Cython

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