Open AccessDigital PCR Fluorescence Image Segmentation Algorithm Based on Image Processing
Author(s) -
Honghui Mu,
Jiayan Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1881/2/022031
Subject(s) - segmentation , artificial intelligence , otsu's method , computer science , computer vision , pixel , image segmentation , pattern recognition (psychology) , fluorescence , digital image , sampling (signal processing) , digital polymerase chain reaction , image processing , image (mathematics) , polymerase chain reaction , chemistry , physics , optics , filter (signal processing) , biochemistry , gene
Digital PCR (Droplet digital Polymerase Chain Reaction) technology is currently one of the mainstream technologies for the detection and quantification of nucleic acid samples. This technology is widely used in the field of molecular biology. This technology counts the number of negative and positive reaction chambers in fluorescent images, and realizes absolute quantification of nucleic acid molecules. Due to the influence of the sampling equipment, some fluorescent images have uneven illumination, and the sampled droplet images will have bad spots and large areas of bright spots. The traditional Otsu segmentation algorithm cannot achieve the ideal segmentation effect. Aiming at the problem of under-segmentation of fluorescent images with uneven illumination using the traditional Otsu method, this paper proposes an algorithm for local segmentation based on Otsu segmentation. This algorithm realizes the segmentation of fluorescent images with uneven illumination and detects bright spots in large areas. The problems of dead pixel removal and scratch processing have been well resolved.