Neural network-based processing and reconstruction of compromised biophotonic image data
Abstract In recent years, ACAI RICH the integration of deep learning techniques with biophotonic setups has opened new horizons in bioimaging.A compelling trend in this field involves deliberately compromising certain measurement metrics to engineer better bioimaging tools in terms of e.g., cost, speed, and form-factor, followed by compensating for