DL-SMLM: a biological imaging dataset containing paired widefield and SMLM super-resolution images

DL-SMLM is a biological image dataset provided for deep-learning super-resolution microscopy, specially methods enabled by single-molecule localization microscopy (SMLM). DL-SMLM provides aligned low-resolution (LR) and high-resolution (HR) image pairs of subcellular structures in fixed cells, acquired from total internal reflection fluorescence microscopy (TIRF) and SMLM, respectively. This dataset consists of five biological structures: CCPs (clathrin heavy chain), ER membrane (sec61β), ER lumen (KDEL), microtubules (MAP7), and mitochondria outer membrane (TOMM20). For each LR image data, we provide a raw image stack with 100 frames captured at 50 ms per frame, which allows users to generate images with different signal-to-noise ratios. For each SR image data, we provide a reconstruction image (8× magnification) and a raw localization data, which allows users to generate customized SMLM reconstructions with different amplifications. For more information about DL-SMLM, please contact us. Please contact the author by e-mail [e-mail].