Showing papers on "Optical tomography published in 2022"

Self-Training Strategy Based on Finite Element Method for Adaptive Bioluminescence Tomography Reconstruction

Abstract: Bioluminescence tomography (BLT) is a promising pre-clinical imaging technique for a wide variety of biomedical applications, which can non-invasively reveal functional activities inside living animal bodies through the detection of visible or near-infrared light produced by bioluminescent reactions. Recently, reconstruction approaches based on deep learning have shown great potential in optical tomography modalities. However, these reports only generate data with stationary patterns of constant target number, shape, and size. The neural networks trained by these data sets are difficult to reconstruct the patterns outside the data sets. This will tremendously restrict the applications of deep learning in optical tomography reconstruction. To address this problem, a self-training strategy is proposed for BLT reconstruction in this paper. The proposed strategy can fast generate large-scale BLT data sets with random target numbers, shapes, and sizes through an algorithm named random seed growth algorithm and the neural network is automatically self-trained. In addition, the proposed strategy uses the neural network to build a map between photon densities on surface and inside the imaged object rather than an end-to-end neural network that directly infers the distribution of sources from the photon density on surface. The map of photon density is further converted into the distribution of sources through the multiplication with stiffness matrix. Simulation, phantom, and mouse studies are carried out. Results show the availability of the proposed self-training strategy.

Monte Carlo-based data generation for efficient deep learning reconstruction of macroscopic diffuse optical tomography and topography applications

Abstract: Deep learning (DL) models are being increasingly developed to map sensor data to the image domain directly. However, DL methodologies are data-driven and require large and diverse data sets to provide robust and accurate image formation performances. For research modalities such as 2D/3D diffuse optical imaging, the lack of large publicly available data sets and the wide variety of instrumentation designs, data types, and applications leads to unique challenges in obtaining well-controlled data sets for training and validation. Meanwhile, great efforts over the last four decades have focused on developing accurate and computationally efficient light propagation models that are flexible enough to simulate a wide variety of experimental conditions.Recent developments in Monte Carlo (MC)-based modeling offer the unique advantage of simulating accurately light propagation spatially, temporally, and over an extensive range of optical parameters, including minimally to highly scattering tissue within a computationally efficient platform. Herein, we demonstrate how such MC platforms, namely "Monte Carlo eXtreme" and "Mesh-based Monte Carlo," can be leveraged to generate large and representative data sets for training the DL model efficiently.We propose data generator pipeline strategies using these platforms and demonstrate their potential in fluorescence optical topography, fluorescence optical tomography, and single-pixel diffuse optical tomography. These applications represent a large variety in instrumentation design, sample properties, and contrast function.DL models trained using the MC-based in silico datasets, validated further with experimental data not used during training, show accurate and promising results.Overall, these MC-based data generation pipelines are expected to support the development of DL models for rapid, robust, and user-friendly image formation in a wide variety of applications.

Normalization of optical fluence distribution for three-dimensional functional optoacoustic tomography of the breast

Abstract: Significance: In three-dimensional (3D) functional optoacoustic tomography (OAT), wavelength-dependent optical attenuation and nonuniform incident optical fluence limit imaging depth and field of view and can hinder accurate estimation of functional quantities, such as the vascular blood oxygenation. These limitations hinder OAT of large objects, such as a human female breast. Aim: We aim to develop a measurement-data-driven method for normalization of the optical fluence distribution and to investigate blood vasculature detectability and accuracy for estimating vascular blood oxygenation. Approach: The proposed method is based on reasonable assumptions regarding breast anatomy and optical properties. The nonuniform incident optical fluence is estimated based on the illumination geometry in the OAT system, and the depth-dependent optical attenuation is approximated using Beer–Lambert law. Results: Numerical studies demonstrated that the proposed method significantly enhanced blood vessel detectability and improved estimation accuracy of the vascular blood oxygenation from multiwavelength OAT measurements, compared with direct application of spectral linear unmixing without optical fluence compensation. Experimental results showed that the proposed method revealed previously invisible structures in regions deeper than 15 mm and/or near the chest wall. Conclusions: The proposed method provides a straightforward and computationally inexpensive approximation of wavelength-dependent effective optical attenuation and, thus, enables mitigation of the spectral coloring effect in functional 3D OAT imaging.

X-ray computed 𝜇-tomography for thecharacterization of optical fibers

Abstract: In spite of their ubiquitous applications, the characterization of glass fibers by means of all-optical techniques is still facing some limitations. Recently, X-ray absorption has been proposed as a method for visualizing the inner structure of both standard and microstructure optical fibers. Here, we exploit X-ray absorption as nondestructive technique for the characterization of glass optical fibers. Starting from absorption contrast X-ray computed micro-tomography measurements, we obtain information about the spatial profile of the fiber refractive index at optical frequencies. We confirm the validity of our approach by comparing its results with complementary characterization techniques, based on electron spectroscopy or multiphoton microscopy.

Computed tomography in resolving flame topology with internal optical blockage involved.

Abstract: This work reports the modification and optimization of a computed tomography (CT) algorithm to become capable of resolving an optical field with internal optical blockage (IOB) present. The IOB-practically, the opaque mechanical parts installed inside the measurement domain-prevents a portion of emitted light from transmitting to optical sensors. Such blockage disrupts the line-of-sight intensity integration on recorded projections and eventually leads to incorrect reconstructions. In the modified algorithm developed in this work, the positions of the obstacle are measured a priori, and then the discretized optical fields (i.e., voxels) are classified as those that participate in the CT process (named effective voxels) and those that are expelled, based on the relative positions of the imaging sensors, IOB, and light signal distribution. Finally, the effective voxels can be iteratively reconstructed by combining their projections on sensors that provide direct observation. Moreover, the impact of IOB on reconstruction accuracy is discussed under different sensor arrangements to provide hands-on guidance on sensor orientation selection in practical CT problems. The modified algorithm and sensor arrangement strategy are both numerically and experimentally validated by simulated phantoms and a two-branch premixed laminar flame in this work.

Spectroscopic thermo-elastic optical coherence tomography for tissue characterization

Abstract: Optical imaging techniques that provide free space, label free imaging are powerful tools in obtaining structural and biochemical information in biological samples. To date, most of the optical imaging technologies create images with a specific contrast and require multimodality integration to add additional contrast. In this study, we demonstrate spectroscopic Thermo-elastic Optical Coherence Tomography (TE-OCT) as a potential tool in tissue identification. TE-OCT creates images based on two different forms of contrast: optical reflectance and thermo-elastic deformation. TE-OCT uses short laser pulses to induce thermo-elastic tissue deformation and measures the resulting surface displacement using phase-sensitive OCT. In this work we characterized the relation between thermo-elastic displacement and optical absorption, excitation, fluence and illumination area. The experimental results were validated with a 2-dimensional analytical model. Using spectroscopic TE-OCT, the thermo-elastic spectra of elastic phantoms and tissue components in coronary arteries were extracted. Specific tissue components, particularly lipid, an important biomarker for identifying atherosclerotic lesions, can be identified in the TE-OCT spectral response. As a label-free, free-space, dual-contrast, all-optical imaging technique, spectroscopic TE-OCT holds promise for biomedical research and clinical pathology diagnosis.

Dispersion Measurement with Optical Computing Optical Coherence Tomography

Abstract: We propose a novel technique to measure fiber dispersion without any derivative operation and index measurement. Based on the relationship between the dispersion and the signal in optical computing optical coherence tomography, dispersion can be deduced with high accuracy from optical computing OCT signal position and resolution. The group velocity dispersion and third order dispersion of single mode fiber and dispersion compensating fiber with lengths of 10 m–10 km are measured to be in good consistence with the nominal value.

Speckle-resolved optical coherence tomography for mesoscopic imaging within scattering media.

Abstract: Light scattering poses a challenge for imaging deep in scattering media as the ballistic light exponentially attenuates with depth. In contrast to the ballistic light, the multiply scattered light penetrates deeper and also contains information about the sample. One technique to image deeper is to selectively detect only a subset of the multiply scattered light, namely the 'snake' photons, which are predominantly forward scattered and retain more direct information than the more strongly scattered light. In this work, we develop a technique, termed speckle-resolved optical coherence tomography (srOCT), for efficiently detecting these 'snake' photons to enable imaging deeper in scattering media. The system couples spatio-angular filtering with speckle-resolved interferometric detection to preferentially and efficiently detect the weakly scattered 'snake' photons. With our proof-of-concept system, we demonstrate depth-resolved imaging beyond the ballistic limit, up to a depth of 90 round-trip MFPs in a scattering phantom and a depth of 4.5 mm of chicken tissue at 0.4 mm axial and lateral resolution.

Wide-field Diffuse Optical Tomography Using Deep Learning

Abstract: A modified AUTOMAP architecture, with micro-CT validation, is used for 3D reconstructions in Diffuse Optical Tomography, employing wide-field illumination and detection. The performance is compared with a regularized Least Squares technique.

Sub-mm resolution tomographic imaging in turbid media by an ultra-high density multichannel approach.

Abstract: We demonstrate an ultra-high-density source-detector (SD) diffuse optical tomography system scalable to thousands of combinatorial SD pairs per cm3 of total voxel volume. We demonstrate the imaging of dynamic targets (including phantom arteries) with 100 um resolution at over 10 Hz frame rate within turbid media (> 60 MFP). Further, as a step toward a wearable mobile imager, we introduce monolithic mm-size dense semiconductor laser array chips as sources for potential unobtrusive epidermal tomographic use.

Estimating optical parameters of biological tissues with photon-counting micro-CT.

Abstract: Wavelength-dependent absorption and scattering properties determine the fluorescence photon transport in biological tissues and image resolution of optical molecular tomography. Currently, these parameters are computed from optically measured data. For small animal imaging, estimation of optical parameters is a large-scale optimization problem, which is highly ill-posed. In this paper, we propose a new, to the best of our knowledge, approach to estimate optical parameters of biological tissues with photon-counting micro-computed tomography (micro-CT). From photon-counting x-ray data, multi-energy micro-CT images can be reconstructed to perform multi-organ segmentation and material decomposition in terms of tissue constituents. The concentration and characteristics of major tissue constituents can be utilized to calculate the optical absorption and scattering coefficients of the involved tissues. In our study, we perform numerical simulation, phantom experiments, and in vivo animal studies to calculate the optical parameters using our proposed approach. The results show that our approach can estimate optical parameters of tissues with a relative error of <10%, accurately mapping the optical parameter distributions in a small animal.

Simple Characterization Scheme for Optical Coherence Tomography Systems With Application to a Commercial and a Near-Isometric Resolution Fibre-Based System

Abstract: Optical Coherence Tomography (OCT) is a rapidly growing imaging modality in biomedical optics. OCT can perform high-resolution, cross-sectional imaging of the microstructure of biological tissues by measuring the coherent spectrum from the backscattered light. OCT systems with broad spectral bandwidths are often constructed using free-space optics to avoid dispersion by fibre optic components. This paper presents a fibre-based OCT system at a centre wavelength of 1300 nm with an axial resolution of 3.8 µm in air, surpassing any previously reported values to the best of our knowledge. Despite the challenges in transporting a broadband spectrum using fibre-optics, the system investigation was motivated by the ever-increasing demand for commercialization of high-resolution OCT systems and simplification of construction. We also evaluate and demonstrate the direct measurement method for axial resolution using an air wedge. Imaging of biomedical and other samples is demonstrated using a high numerical aperture sample lens and compared with images from a commercial OCT system. We discuss the effect of the improved structural visibility by achieving image voxels closer to an isometric shape with a high NA sample lens.

Co-registered speckle contrast optical tomography and frequency domain-diffuse optical tomography for imaging of the fifth metatarsal.

Abstract: A co-registered speckle contrast optical tomography and frequency domain-diffuse optical tomography system has been designed for imaging total hemoglobin concentration, blood oxygenation, and blood flow with the future aim of monitoring Jones fractures of the fifth metatarsal. Experimental validation was performed using both in vitro tissue-mimicking phantoms and in vivo cuff occlusion experiments. Results of these tissue phantom experiments ensure accurate recovery of three-dimensional distributions of optical properties and flow. Finally, cuff occlusion experiments performed on one healthy human subject demonstrate the system's ability to recover both decreasing tissue oxygenation and blood flow as caused by an arterial occlusion.

Single-shot off-axis full-field optical coherence tomography

Abstract: Full field optical coherence tomography (FF-OCT) enables high-resolution in-depth imaging within turbid media. In this work, we present a simple approach which combines FF-OCT with off-axis interferometry for reconstruction of en-face images. With low spatial and temporal coherence illumination, this method is able to extract an FF-OCT image from only one interference acquisition. This method is described, and the proof-of-concept is demonstrated through the observation of scattering samples such as organic and ex vivo biomedical samples.

Evaluation of a pipeline for simulation, reconstruction, and classification in ultrasound-aided diffuse optical tomography of breast tumors

Abstract: Significance: Diffuse optical tomography is an ill-posed problem. Combination with ultrasound can improve the results of diffuse optical tomography applied to the diagnosis of breast cancer and allow for classification of lesions. Aim: To provide a simulation pipeline for the assessment of reconstruction and classification methods for diffuse optical tomography with concurrent ultrasound information. Approach: A set of breast digital phantoms with benign and malignant lesions was simulated building on the software VICTRE. Acoustic and optical properties were assigned to the phantoms for the generation of B-mode images and optical data. A reconstruction algorithm based on a two-region nonlinear fitting and incorporating the ultrasound information was tested. Machine learning classification methods were applied to the reconstructed values to discriminate lesions into benign and malignant after reconstruction. Results: The approach allowed us to generate realistic US and optical data and to test a two-region reconstruction method for a large number of realistic simulations. When information is extracted from ultrasound images, at least 75% of lesions are correctly classified. With ideal two-region separation, the accuracy is higher than 80%. Conclusions: A pipeline for the generation of realistic ultrasound and diffuse optics data was implemented. Machine learning methods applied to a optical reconstruction with a nonlinear optical model and morphological information permit to discriminate malignant lesions from benign ones.

Effect of modulation frequency on image quality in frequency domain high-density diffuse optical tomography in infant head

Abstract: We investigated image quality of frequency domain high-density diffuse optical tomography with multiple modulation frequencies in infant head model. We found image quality and field of view are optimized between 300~400 MHz when considering noise.

Evaluation of Signal Degradation Due to Birefringence in a Multiple Reference Optical Coherence Tomography System With Polarization-Based Balanced Detection

Abstract: Although time-domain optical coherence tomography (TD-OCT) systems are straightforward to realize, the imaging speed, sensitivity, and imaging depth limit their range of applications. Multiple reference optical coherence tomography (MR-OCT) based on TD-OCT increases imaging range by about tenfold while providing sensitivity to image highly scattering biological samples. The multiple path-delays and free-space construction make MR-OCT also interesting for hybrid and compact systems, filling the gap between fibre-based and wafer-level integrated optical systems. We describe an optical configuration using a balanced detection scheme and the resulting signal properties due to the required use of polarizing optical components. We numerically simulate the signal properties using Jones calculus and compare the results with measurements. We discuss the origin of signal degradation due to birefringence of the sample in OCT and show that the quarter-wave plate in the sample arm of the Michelson interferometer can be adjusted to optimize the signal returning from a birefringent sample thereby improving the visibility of structures of interest. The theory discussed will be useful to understand and minimize signal degradation due to birefringence in Time-Domain and Fourier-Domain OCT systems.

Image enhancement for optical coherence tomography with super-resolution generative adversarial networks (SRGAN)

Abstract: We present a novel approach of leveraging deep learning to reconstruct high-resolution OCT B-scans from reduced axial resolution data. In this work, the original OCT signal is used as the ground truth, and lower resolution was simulated by windowing the interference fringes. A super-resolution pixel-to-pixel generative adversarial network (GAN) was investigated for reconstructing high-resolution OCT data in the spatial domain and is compared against reconstructing in the spectral domain.

Full field optical transmission tomography (FFOTT) of biological samples: Static and dynamic approaches

Abstract: Whereas Full Field OCT (FFOCT) relies on backscattering of light, Full Field Optical Transmission Tomography (FFOTT) relies on forward scattering using the Gouy’s phase shift modulation that is achieved close to the focus of a microscope objective. This new type of endogenous cell imaging technique that offers structural and metabolic contrasts is particularly well suited for imaging cell culture on glass slide or Petri dishes avoiding fringes that mask cells in FFOCT as well as biological structures such as biofilms. The sectioning ability is close to confocal microscopy but no contrast agent is required.

Source polarisation independent single-shot cross-polarised optical coherence tomography approaches: a comparison

Abstract: We have developed several methods to realise a cross-polarised optical coherence tomography system that works independent of the polarisation state of the source. Here, we compare the performance of these approaches.

Fourier-domain mode-locked laser-based optical coherence tomography system with large imaging depth

Abstract: A frequency swept source optical coherence tomography (OCT) imaging system is proposed. The frequency swept source used in the system is a Fourier-domain mode-locked (FDML) laser which has a narrow instantaneous linewidth due to the nonlinear spectrum narrowing effect generated by the nonlinear semiconductor optical amplifier (SOA) used in the FDML laser ring cavity. Therefore, the OCT imaging system has the ability to achieve a large imaging depth. The concept is verified in the experiment, which demonstrates a clear two-dimensional target image and a large imaging depth up to 14 mm.

Multi-focus average for multiple noise suppression in optical coherence tomography

Abstract: We propose a new multi-focus average method for optical coherence tomography, which reduces the multiple scattering signals and improves the visibility of sample structure in deep region. A phantom and zebrafish were used for validation.

Laser Computed Tomography and Transillumination Imaging with Coherent Detection Imaging Techniques

Abstract: This paper reports our recent study on laser computed tomography and transillumination/projection imaging achieved by Coherent Detection Imaging (CDI) method. Experimental results using biological tissues and samples are presented by this method incorporating the optical heterodyne detection technique and the image reconstruction based on the projection slice theorem.

Deep physics prior for optical diffraction tomography

Abstract: We propose a physics-informed neural network for the scattering problem from biological samples. We use this network as a forward model in an optimization task for optical diffraction tomography to reconstruct the refractive index distribution.

Enabling hyperspectral acquisition for scanning laser optical tomography

Abstract: Scanning Laser Optical Tomography (SLOT) is a three-dimensional imaging technique usable on a micro- to mesoscale. The technique is equivalent to computer tomography, using a laser instead of x-rays. With this technology, a set of twodimensional images is acquired at different angles and subsequently processed into volume information by reconstruction algorithms. Different contrast mechanisms can be used, depending on the application. Up until now transmission, scattering, fluorescence and second harmonic generation have been established for SLOT imaging. All of these contrast mechanisms are coupled to a specific narrow bandwidth, which is determined before the acquisition starts and is dependent on the setup and application. In order to collect true hyperspectral information, a spectrometer and a broadband light source have been integrated. This way, the amount of information is increased with each measurable wavelength, leading to various improvements of the SLOT technology. The entire transmission and absorption spectra of three-dimensional samples can now be measured and reconstructed. Here, we present the current state of development of the hyperspectral SLOT. This includes the technical construction of the hardware setup and the development of the software integration. Many challenges need to be overcome when implementing spectroscopy in a tomographic setup. Solutions to specific problems, such as decreased resolution and focal shift, will be presented. Finally, we will show the first results of hyperspectral SLOT imaging.

Micron-resolution Optical Coherence Tomography of the Human Eye

Abstract: We have developed a new technique for micron scale resolution cross-sectional imaging in biological systems called Optical Coherence Tomography (OCT)1,2 In OCT, low-coherence optical interferometry3,4 is used to resolve the position of reflective or optical backscattering sites within a sample. Two-dimensional tomographic images of a thin, optical slice of tissue may be obtained with 10 μm longitudinal and lateral resolution. Narrowband optical heterodyne detection achieves a sensitivity to reflected light as small as 10-10 of the incident optical power. OCT is non-contact, non-invasive, and has superior resolution to conventional clinical ultrasound. Unlike scanning laser ophthalmoscopy and scanning laser tomography, the optical sectioning capability of OCT is not restricted by the pupil-limited numerical aperture of the eye or ocular aberrations. OCT may be implemented in a compact, low-cost, fiber-optic based interferometer that is easily coupled to existing ophthalmic instrumentation. We demonstrate high-speed, in vivo OCT imaging in both the anterior and posterior eye.

Volumetric differential-phase imaging in scattering mode by optical coherence tomography

Abstract: We demonstrate volumetric phase contrast imaging by using optical coherence tomography (OCT). In general, the randomness of the scatterers’ distribution prohibits the volumetric measurement of a meaningful phase in a scattering mode. Our method uses complex numerical manipulation of an en-face complex OCT and gives a transversally differential phase image similar to a differential interference contrast microscope (DIC). Not like the DIC, our method can arbitrarily select the amount and direction of the shear after the OCT acquisition. In addition it provides DIC-like images at arbitrary depths. This method is validated by using a 840-nm spectral domain OCT system. A zebrafish sample is measured over a 1-mm × 1-mm transversal scanning range.

Iterative optical diffraction tomography with embedded regularization.

Abstract: Total-variation regularization is applied at each iteration of an iterative framework for optical diffraction tomography. Numerical and experimental tests are performed using various highly scattering objects, and significant improvement in reconstruction SNR are demonstrated.