In solid oncology,on fluorescence microscopy images of interphase nuclei processed with fluorescence in situ hybridization(FISH)technology,DNA amplification often appears as diffraction-limited blobs.Imaging conditions limit image quality,resulting in a low image signal-to-noise ratio of the image,serious background interference,and non-blob structure interference.Designing suitable blob detection methods to provide objective and quantitative data helps doctors diagnose cancer.The algorithm first uses three-layer wavelet multiscale summation to denoise the fluorescence image,then uses the multiscale Laplacian of Gaussian operator to enhance the blob area,and finally suppresses the non-blob area through unilateral second-order Gaussian kernels in four directions to complete blob detection.Experimental results show that for 83 images in the self-built database,the average F-score reaches 0.96,and the average running time is less than 0.5 s.
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