Comparative analysis of full-field OCT and optical transmission tomography

Label-Free Optical Transmission Tomography for Direct Mycological Examination and Monitoring of Intracellular Dynamics

Live-cell imaging generally requires pretreatment with fluorophores to either monitor cellular functions or the dynamics of intracellular processes and structures. We have recently introduced full-field optical coherence tomography for the label-free live-cell imaging of fungi with potential clinical applications for the diagnosis of invasive fungal mold infections. While both the spatial resolution and technical set up of this technology are more likely designed for the histopathological analysis of tissue biopsies, there is to our knowledge no previous work reporting the use of a light interference-based optical technique for direct mycological examination and monitoring of intracellular processes. We describe the first application of dynamic full-field optical transmission tomography (D-FF-OTT) to achieve both high-resolution and live-cell imaging of fungi. First, D-FF-OTT allowed for the precise examination and identification of several elementary structures within a selection of fungal species commonly known to be responsible for invasive fungal infections such as Candida albicans, Aspergillus fumigatus, or Rhizopus arrhizus. Furthermore, D-FF-OTT revealed the intracellular trafficking of organelles and vesicles related to metabolic processes of living fungi, thus opening new perspectives in fast fungal infection diagnostics.

Optical tomography in a single camera frame using fringe-encoded deep-learning full-field OCT

Optical coherence tomography is a valuable tool for in vivo examination thanks to its superior combination of axial resolution, field-of-view and working distance. OCT images are reconstructed from several phases that are obtained by modulation/multiplexing of light wavelength or optical path. This paper shows that only one phase (and one camera frame) is sufficient for en face tomography. The idea is to encode a high-frequency fringe patterns into the selected layer of the sample using low-coherence interferometry. These patterns can then be efficiently extracted with a high-pass filter enhanced via deep learning networks to create the tomographic full-field OCT view. This brings 10-fold improvement in imaging speed, considerably reducing the phase errors and incoherent light artifacts related to in vivo movements. Moreover, this work opens a path for low-cost tomography with slow consumer cameras. Optically, the device resembles the conventional time-domain full-field OCT without incurring additional costs or a field-of-view/resolution reduction. The approach is validated by imaging in vivo cornea in human subjects. Open-source and easy-to-follow codes for data generation/training/inference with U-Net/Pix2Pix networks are provided to be used in a variety of image-to-image translation tasks.

30 Years of Optical Coherence Tomography: introduction to the feature issue

The guest editors introduce a feature issue commemorating the 30th anniversary of Optical Coherence Tomography.