面向荧光显微图像的斑点检测  

Blob Detection for Fluorescence Microscopy Image

作　　者：何柯材 徐琳 江金康 陶禹川 王学渊[1] HE Ke-Cai;XU Lin;JIANG Jin-Kang;TAO Yu-Chuan;WANG Xue-Yuan(School of Information Engineering,Southwest University of Science and Technology,Mianyang 621000,China;School of Management and Economics,Beijing University of Chemical Technology,Beijing 100029,China)

机构地区：[1]西南科技大学信息工程学院,绵阳621000 [2]北京化工大学经济管理学院,北京100029

出　　处：《计算机系统应用》2024年第8期205-213,共9页Computer Systems & Applications

基　　金：四川省自然科学基金(2023NSFSC0466)。

摘　　要：实体肿瘤学中,利用荧光原位杂交(FISH)技术处理后的间期细胞核荧光显微图像上,DNA扩增往往呈现为衍射极限斑点,成像条件限制了图像质量,导致图像信噪比较低、背景干扰严重且存在非斑点结构干扰.设计适用的斑点检测方法,提供客观且定量的数据,有助于医生对于癌症病情的诊断.算法首先采用3层小波多尺度求和对荧光图像去噪,随后利用多尺度高斯拉普拉斯算子增强斑点区域,最后通过4个方向的单边二阶高斯核抑制非斑点区域,完成斑点检测.实验结果表明,对于自建数据库中83张图像,算法平均F分数达到0.96,平均运行时间0.5 s以下.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.

关 键 词：荧光显微图像 斑点检测 图像降噪 图像增强 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] R318[自动化与计算机技术—计算机科学与技术]