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Cell detection in very low contrast images using discrete curvelet transform and radon transform with morphological operations

机译:使用离散曲线变换和氡变换与形态学操作非常低的对比图像中的细胞检测

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Cell detection has been a crucial area in modern cell image processing applications. The low contrast cell images is a major limitation in cell detection. This paper proposes a method to detect cells in very low contrast cell images using Fast Discrete Curvelet Transform (FDCT), radon transform and morphological operations by reconstruction. The contrast of the cell images is improved by nonlinearly modifying the curvelet coefficients at selective scales. Further, radon transform is applied to reconstruct the image from the preprocessed image. Finally, the optimum morphological operations have been applied on the processed images to extract the cell regions from the low contrast cell images. The proposed method has been tested and improved cell detection results have been obtained.
机译:细胞检测是现代细胞图像处理应用中的关键区域。低对比度细胞图像是细胞检测的一个主要限制。本文提出了一种使用快速离散的Curvelet变换(FDCT),Radon变换和形态学操作来检测非常低对比度小区图像中的细胞的方法。通过在选择度尺度处非线性地修改Curvelet系数来改善细胞图像的对比度。此外,应用氡变换以从预处理的图像重建图像。最后,已经在处理的图像上应用了最佳的形态学操作以从低对比度小区图像中提取小区区域。已经测试了所提出的方法,并获得了改善的细胞检测结果。

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