Edge-Enabled Anti-Noise Telepathology Imaging Reconstruction Technology in Harsh Environments

With the advent of the 5G era, telemedicine and mobile health play an increasingly important role in our daily lives. In the diagnosis process of telemedicine, image processing of telepathology is particularly important to doctors, pathologists, and relevant researchers. In this article, we propose an intelligent telepathology imaging terminal system, the images of which are obtained by Fourier ptychographic microscopy (FPM). For the proposed system, a CNN model is designed and trained to perform the FPM reconstruction to increase the quality of the images and improve the speed of reconstruction. Furthermore, edge learning technology is used in the proposed system to reduce the pressure of data storage and transmission. The proposed scheme is applied in harsh communication environments of low signal-to-noise ratio. The theoretical analysis and experimental results show that the proposed system achieves high-quality digital images and phase maps of histological samples.