Computed Optical Interferometric Imaging: Methods, Achievements, and Challenges

Recent Advances and Current Trends in Transmission Tomographic Diffraction Microscopy

Optical microscopy techniques are among the most used methods in biomedical sample characterization. In their more advanced realization, optical microscopes demonstrate resolution down to the nanometric scale. These methods rely on the use of fluorescent sample labeling in order to break the diffraction limit. However, fluorescent molecules' phototoxicity or photobleaching is not always compatible with the investigated samples. To overcome this limitation, quantitative phase imaging techniques have been proposed. Among these, holographic imaging has demonstrated its ability to image living microscopic samples without staining. However, for a 3D assessment of samples, tomographic acquisitions are needed. Tomographic Diffraction Microscopy (TDM) combines holographic acquisitions with tomographic reconstructions. Relying on a 3D synthetic aperture process, TDM allows for 3D quantitative measurements of the complex refractive index of the investigated sample. Since its initial proposition by Emil Wolf in 1969, the concept of TDM has found a lot of applications and has become one of the hot topics in biomedical imaging. This review focuses on recent achievements in TDM development. Current trends and perspectives of the technique are also discussed.

Combined hardware and computational optical wavefront correction

In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of in vivo human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.

Wavefront measurement using computational adaptive optics

In many optical imaging applications, it is necessary to correct for aberrations to obtain high quality images. Optical coherence tomography (OCT) provides access to the amplitude and phase of the backscattered optical field for three-dimensional (3D) imaging samples. Computational adaptive optics (CAO) modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations without using a deformable mirror, as is commonly done in hardware-based adaptive optics (AO). This provides improvement of image quality throughout the 3D volume, enabling imaging across greater depth ranges and in highly aberrated samples. However, the CAO aberration correction has a complicated relation to the imaging pupil and is not a direct measurement of the pupil aberrations. Here we present new methods for recovering the wavefront aberrations directly from the OCT data without the use of hardware adaptive optics. This enables both computational measurement and correction of optical aberrations.

Agreement in Cone Density Derived from Gaze-Directed Single Images Versus Wide-Field Montage Using Adaptive Optics Flood Illumination Ophthalmoscopy

Purpose

We compared cone density measurements derived from the center of gaze-directed single images with reconstructed wide-field montages using the rtx1 adaptive optics (AO) retinal camera.

Methods

A total of 29 eyes from 29 healthy subjects were imaged with the rtx1 camera. Of 20 overlapping AO images acquired, 12 (at 3.2°, 5°, and 7°) were used for calculating gaze-directed cone densities. Wide-field AO montages were reconstructed and cone densities were measured at the corresponding 12 loci as determined by field projection relative to the foveal center aligned to the foveal dip on optical coherence tomography. Limits of agreement in cone density measurement between single AO images and wide-field AO montages were calculated.

Results

Cone density measurements failed in 1 or more gaze directions or retinal loci in up to 58% and 33% of the subjects using single AO images or wide-field AO montage, respectively. Although there were no significant overall differences between cone densities derived from single AO images and wide-field AO montages at any of the 12 gazes and locations (P = 0.01-0.65), the limits of agreement between the two methods ranged from as narrow as -2200 to +2600, to as wide as -4200 to +3800 cones/mm².

Conclusions

Cone density measurement using the rtx1 AO camera is feasible using both methods. Local variation in image quality and altered visibility of cones after generating montages may contribute to the discrepancies.

Translational Relevance

Cone densities from single AO images are not interchangeable with wide-field montage derived-measurements.

Interferometric synthetic aperture microscopy for extended focus optical coherence microscopy

Optical coherence microscopy (OCM) is an interferometric technique providing 3D images of biological samples with micrometric resolution and penetration depth of several hundreds of micrometers. OCM differs from optical coherence tomography (OCT) in that it uses a high numerical aperture (NA) objective to achieve high lateral resolution. However, the high NA also reduces the depth-of-field (DOF), scaling with 1/NA². Interferometric synthetic aperture microscopy (ISAM) is a computed imaging technique providing a solution to this trade-off between resolution and DOF. An alternative hardware method to achieve an extended DOF is to use a non-Gaussian illumination. Extended focus OCM (xfOCM) uses a Bessel beam to obtain a narrow and extended illumination volume. xfOCM detects back-scattered light using a Gaussian mode in order to maintain good sensitivity. However, the Gaussian detection mode limits the DOF. In this work, we present extended ISAM (xISAM), a method combining the benefits of both ISAM and xfOCM. xISAM uses the 3D coherent transfer function (CTF) to generalize the ISAM algorithm to different system configurations. We demonstrate xISAM both on simulated and experimental data, showing that xISAM attains a combination of high transverse resolution and extended DOF which has so far been unobtainable through conventional ISAM or xfOCM individually.

Computational optical coherence tomography [Invited]

Optical coherence tomography (OCT) has become an important imaging modality with numerous biomedical applications. Challenges in high-speed, high-resolution, volumetric OCT imaging include managing dispersion, the trade-off between transverse resolution and depth-of-field, and correcting optical aberrations that are present in both the system and sample. Physics-based computational imaging techniques have proven to provide solutions to these limitations. This review aims to outline these computational imaging techniques within a general mathematical framework, summarize the historical progress, highlight the state-of-the-art achievements, and discuss the present challenges.

Correction of aberrations in the human eye using computational methods

Phase-sensitive imaging and computational correction of patient-specific optical aberrations enable high-resolution imaging of the human retina to aid diagnosis and treatment of eye diseases.