Tensorflow/keras implementation for image transformation from low-resolution (LR) image to super-resolved one, including single wide-field (WF) image super-resolution prediction and SIM reconstruction.
Following is the extract from the paper and i have marked the corresponding files names for CCP's. Seems #2 is not available in the data shared. Is my understanding correct?
1. For each ROI, we acquired nine sets of N-phase × M-orientation raw images with constant 1 ms exposure time but increasing the excitation light intensity, where N and M are three for TIRF-SIM and GI-SIM, and five for nonlinear SIM. - *RawSIMDatalevel.mrc**
2. Meanwhile, each set of N × M raw images was reconstructed into a SIM image attributing the same fluorescence level as the
corresponding WF image, which served as a reference to assess the quality of the
DLSR image at that fluorescence level. - Missing
3 - In addition, in the same ROI, we finally elevated the excitation intensity and exposure time (typically 120 W cm−2 for 10 ms) to achieve a high fluorescence level of >1,200 average photon count, and independently acquired three sets of N × M raw images. The resulting three SIM images of ultrahigh SNR were averaged as the GT-SIM image to guarantee high quality. SIM_gt.mrc
Following is the extract from the paper and i have marked the corresponding files names for CCP's. Seems #2 is not available in the data shared. Is my understanding correct?
1. For each ROI, we acquired nine sets of N-phase × M-orientation raw images with constant 1 ms exposure time but increasing the excitation light intensity, where N and M are three for TIRF-SIM and GI-SIM, and five for nonlinear SIM. - *RawSIMDatalevel.mrc**
2. Meanwhile, each set of N × M raw images was reconstructed into a SIM image attributing the same fluorescence level as the
corresponding WF image, which served as a reference to assess the quality of the DLSR image at that fluorescence level. - Missing
3 - In addition, in the same ROI, we finally elevated the excitation intensity and exposure time (typically 120 W cm−2 for 10 ms) to achieve a high fluorescence level of >1,200 average photon count, and independently acquired three sets of N × M raw images. The resulting three SIM images of ultrahigh SNR were averaged as the GT-SIM image to guarantee high quality. SIM_gt.mrc