Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy.

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations.

Photon Counting: Detectors and Applications.

The editorial introduces the special issue on photon counting detectors and applications.

Utility of photon-counting detectors for MV-kV dual-energy computed tomography imaging.

Purpose: High soft-tissue contrast imaging is essential for effective radiotherapy treatment. This could potentially be realized using both megavoltage and kilovoltage x-ray sources available on some therapy treatment systems to perform "MV-kV" dual-energy (DE) computed tomography (CT). However, noisy megavoltage images obtained with existing energy-integrating detectors (EIDs) are a limiting factor for clinical translation.

Evaluation of waning of IgG antibody responses after rVSVΔG-ZEBOV-GP and Ad26.ZEBOV, MVA-BN-Filo Ebola virus disease vaccines: a modelling study from the PREVAC randomized trial.

rVSVΔG-ZEBOV-GP and Ad26.ZEBOV, MVA-BN-Filo are WHO-prequalified vaccination regimens against Ebola virus disease (EVD). Challenges associated with measuring long-term clinical protection warrant the evaluation of immune response kinetics after vaccination.