The application discloses a
bladder cancer cell segmentation method and device based on
urine sediment microscopy and a storage medium; the method comprises the following steps: taking a
urine sediment microscopy image as an input image, inputting the input image into a detection model, marking a high-suspected
cancer cell area in the input image through the detection model, and generating a boundary box; segmenting the high-suspected
cancer cell area in the boundary box through a segmentation model, obtaining a
mask of each
cancer cell, deleting the corresponding boundary box if the
mask is empty or the
area ratio is lower than a preset threshold, mapping the effective
mask back to the input image, merging all the effective masks, and generating a segmentation result of the cancer cells. The detection model can effectively reduce the
processing range of the segmentation model, avoid the waste of computing resources caused by full-image search, and improve the
processing speed. The segmentation model can automatically filter out
false detection or invalid areas, and ensure the accuracy and reliability of the segmentation result.