Convolutional neural network-based kidney tubule epithelial cell automatic detection method
A convolutional neural network and epithelial cell technology, applied in the field of automatic detection of renal tubular epithelial cells, can solve problems such as easy fatigue, missed detection, and false detection, and achieve the effect of avoiding low efficiency
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[0034] Below in conjunction with accompanying drawing, a kind of automatic detection method of renal tubular epithelial cell based on convolutional neural network of the present invention is described in detail:
[0035] Step 1: Use a microscope to collect several medical microscopic grayscale images;
[0036] Step 2: Perform median filtering on the obtained grayscale image;
[0037] Step 2-1: Slide the 3×3 filter window as a template on the original image, and the center position of the filter window is the target pixel to be processed by the filter;
[0038] Step 2-2: Sort the pixel gray values in the filtering window according to their size to obtain the median value, and assign the obtained median value to the original target pixel;
[0039] Step 2-3: After the target pixel gets a new gray value, check whether the image has been traversed and calculated. If there are still pixels in the image that have not been calculated, return to continue sliding the filter window to...
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