Fig. 9From: Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy imagesDenoising super-resolution images using UNet. Noisy super-resolution image from our colon tissue dataset (a), noise probability map (b) output from a UNet model trained on similar noise regions from super-resolution images, and the denoised image (c), resulting from subtracting the noise map from the original image in (a)Back to article page