Scanning Laser Optical Tomography Resolves Structural Plasticity during Regeneration in an Insect Brain

Background: Optical Projection Tomography (OPT) is a microscopic technique that generates three dimensional images from whole mount samples the size of which exceeds the maximum focal depth of confocal laser scanning microscopes. As an advancement of conventional emission-OPT, Scanning Laser Optical Tomography (SLOTy) allows simultaneous detection of fluorescence and absorbance with high sensitivity. In the present study, we employ SLOTy in a paradigm of brain plasticity in an insect model system. Methodology: We visualize and quantify volumetric changes in sensory information procession centers in the adult locust, Locusta migratoria. Olfactory receptor neurons, which project from the antenna into the brain, are axotomized by crushing the antennal nerve or ablating the entire antenna. We follow the resulting degeneration and regeneration in the olfactory centers (antennal lobes and mushroom bodies) by measuring their size in reconstructed SLOTy images with respect to the untreated control side. Within three weeks post treatment antennal lobes with ablated antennae lose as much as 60% of their initial volume. In contrast, antennal lobes with crushed antennal nerves initially shrink as well, but regain size back to normal within three weeks. The combined application of transmission-and fluorescence projections of Neurobiotin labeled axotomized fibers confirms that recovery of normal size is restored by regenerated afferents. Remarkably, SLOTy images reveal that degeneration of olfactory receptor axons has a trans-synaptic effect on second order brain centers and leads to size reduction of the mushroom body calyx. Conclusions: This study demonstrates that SLOTy is a suitable method for rapid screening of volumetric plasticity in insect brains and suggests its application also to vertebrate preparations.

Speckle reduction in optical coherence tomography imaging by affine-motion image registration

Signal-degrading speckle is one factor that can reduce the quality of optical coherence tomography images. We demonstrate the use of a hierarchical model-based motion estimation processing scheme based on an affine-motion model to reduce speckle in optical coherence tomography imaging, by image registration and the averaging of multiple B-scans. The proposed technique is evaluated against other methods available in the literature. The results from a set of retinal images show the benefit of the proposed technique, which provides an improvement in signal-to-noise ratio of the square root of the number of averaged images, leading to clearer visual information in the averaged image. The benefits of the proposed technique are also explored in the case of ocular anterior segment imaging.

Optical micro-tomography “OPenT” allows the study of large toadfish Halobatrachus didactylus embryos and larvae

Batrachoidids, which include midshipman and toadfish are less known among embryologists, but are common in other fields. They are characteristic for their acoustic communication, and develop hearing and sound production while young juveniles. They lay large benthic eggs (>5mm) with a thick chorion and adhesive disk and slow development, which are particularly challenging for studying embryology. Here we took advantage of a classical tissue clearing technique and the OPenT open-source platform for optical tomography imaging, to image a series of embryos and larvae from 3 to 30mm in length, which allowed detailed 3D anatomical reconstructions non-destructively. We documented some of the developmental stages (early and late in development) and the anatomy of the delicate stato-acoustic organs, swimming bladder and associated sonic muscles. Compared to other techniques accessible to developmental biology labs, OPenT provided advantages in terms of image quality, cost of operation and data throughput, allowing identification and quantitative morphometrics of organs in larvae, earlier and with higher accuracy than is possible with other imaging techniques.

Convergence analysis of the Newton algorithm and a pseudo-time marching scheme for diffuse correlation tomography

We propose a self-regularized pseudo-time marching scheme to solve the ill-posed, nonlinear inverse problem associated with diffuse propagation of coherent light in a tissuelike object. In particular, in the context of diffuse correlation tomography (DCT), we consider the recovery of mechanical property distributions from partial and noisy boundary measurements of light intensity autocorrelation. We prove the existence of a minimizer for the Newton algorithm after establishing the existence of weak solutions for the forward equation of light amplitude autocorrelation and its Frechet derivative and adjoint. The asymptotic stability of the solution of the ordinary differential equation obtained through the introduction of the pseudo-time is also analyzed. We show that the asymptotic solution obtained through the pseudo-time marching converges to that optimal solution provided the Hessian of the forward equation is positive definite in the neighborhood of optimal solution. The superior noise tolerance and regularization-insensitive nature of pseudo-dynamic strategy are proved through numerical simulations in the context of both DCT and diffuse optical tomography. (C) 2010 Optical Society of America.

Computationally efficient optical tomographic reconstructions through waveletizing the normalized quadratic perturbation equation - art. no.61640R

In this paper, we present a wavelet - based approach to solve the non-linear perturbation equation encountered in optical tomography. A particularly suitable data gathering geometry is used to gather a data set consisting of differential changes in intensity owing to the presence of the inhomogeneous regions. With this scheme, the unknown image, the data, as well as the weight matrix are all represented by wavelet expansions, thus yielding the representation of the original non - linear perturbation equation in the wavelet domain. The advantage in use of the non-linear perturbation equation is that there is no need to recompute the derivatives during the entire reconstruction process. Once the derivatives are computed, they are transformed into the wavelet domain. The purpose of going to the wavelet domain, is that, it has an inherent localization and de-noising property. The use of approximation coefficients, without the detail coefficients, is ideally suited for diffuse optical tomographic reconstructions, as the diffusion equation removes most of the high frequency information and the reconstruction appears low-pass filtered. We demonstrate through numerical simulations, that through solving merely the approximation coefficients one can reconstruct an image which has the same information content as the reconstruction from a non-waveletized procedure. In addition we demonstrate a better noise tolerance and much reduced computation time for reconstructions from this approach.

Elimination of cross-talk in diffuse optical tomographic reconstructions through a weighted update procedure: results of simulation study - art. no. 61640S

Reconstructions in optical tomography involve obtaining the images of absorption and reduced scattering coefficients. The integrated intensity data has greater sensitivity to absorption coefficient variations than scattering coefficient. However, the sensitivity of intensity data to scattering coefficient is not zero. We considered an object with two inhomogeneities (one in absorption and the other in scattering coefficient). The standard iterative reconstruction techniques produced results, which were plagued by cross talk, i.e., the absorption coefficient reconstruction has a false positive corresponding to the location of scattering inhomogeneity, and vice-versa. We present a method to remove cross talk in the reconstruction, by generating a weight matrix and weighting the update vector during the iteration. The weight matrix is created by the following method: we first perform a simple backprojection of the difference between the experimental and corresponding homogeneous intensity data. The built up image has greater weightage towards absorption inhomogeneity than the scattering inhomogeneity and its appropriate inverse is weighted towards the scattering inhomogeneity. These two weight matrices are used as multiplication factors in the update vectors, normalized backprojected image of difference intensity for absorption inhomogeneity and the inverse of the above for the scattering inhomogeneity, during the image reconstruction procedure. We demonstrate through numerical simulations, that cross-talk is fully eliminated through this modified reconstruction procedure.

Accelerated gradient based diffuse optical tomographic image reconstruction

Purpose: Fast reconstruction of interior optical parameter distribution using a new approach called Broyden-based model iterative image reconstruction (BMOBIIR) and adjoint Broyden-based MOBIIR (ABMOBIIR) of a tissue and a tissue mimicking phantom from boundary measurement data in diffuse optical tomography (DOT). Methods: DOT is a nonlinear and ill-posed inverse problem. Newton-based MOBIIR algorithm, which is generally used, requires repeated evaluation of the Jacobian which consumes bulk of the computation time for reconstruction. In this study, we propose a Broyden approach-based accelerated scheme for Jacobian computation and it is combined with conjugate gradient scheme (CGS) for fast reconstruction. The method makes explicit use of secant and adjoint information that can be obtained from forward solution of the diffusion equation. This approach reduces the computational time many fold by approximating the system Jacobian successively through low-rank updates. Results: Simulation studies have been carried out with single as well as multiple inhomogeneities. Algorithms are validated using an experimental study carried out on a pork tissue with fat acting as an inhomogeneity. The results obtained through the proposed BMOBIIR and ABMOBIIR approaches are compared with those of Newton-based MOBIIR algorithm. The mean squared error and execution time are used as metrics for comparing the results of reconstruction. Conclusions: We have shown through experimental and simulation studies that Broyden-based MOBIIR and adjoint Broyden-based methods are capable of reconstructing single as well as multiple inhomogeneities in tissue and a tissue-mimicking phantom. Broyden MOBIIR and adjoint Broyden MOBIIR methods are computationally simple and they result in much faster implementations because they avoid direct evaluation of Jacobian. The image reconstructions have been carried out with different initial values using Newton, Broyden, and adjoint Broyden approaches. These algorithms work well when the initial guess is close to the true solution. However, when initial guess is far away from true solution, Newton-based MOBIIR gives better reconstructed images. The proposed methods are found to be stable with noisy measurement data. (C) 2011 American Association of Physicists in Medicine. DOI: 10.1118/1.3531572]

Implementation of a phase array diffuse optical tomographic imager

Diffuse optical tomography (DOT) using near-infrared (NIR) light is a promising tool for noninvasive imaging of deep tissue. This technique is capable of quantitative reconstructions of absorption coefficient inhomogeneities of tissue. The motivation for reconstructing the optical property variation is that it, and, in particular, the absorption coefficient variation, can be used to diagnose different metabolic and disease states of tissue. In DOT, like any other medical imaging modality, the aim is to produce a reconstruction with good spatial resolution and accuracy from noisy measurements. We study the performance of a phase array system for detection of optical inhomogeneities in tissue. The light transport through a tissue is diffusive in nature and can be modeled using diffusion equation if the optical parameters of the inhomogeneity are close to the optical properties of the background. The amplitude cancellation method that uses dual out-of-phase sources (phase array) can detect and locate small objects in turbid medium. The inverse problem is solved using model based iterative image reconstruction. Diffusion equation is solved using finite element method for providing the forward model for photon transport. The solution of the forward problem is used for computing the Jacobian and the simultaneous equation is solved using conjugate gradient search. The simulation studies have been carried out and the results show that a phase array system can resolve inhomogeneities with sizes of 5 mm when the absorption coefficient of the inhomogeneity is twice that of the background tissue. To validate this result, a prototype model for performing a dual-source system has been developed. Experiments are carried out by inserting an inhomogeneity of high optical absorption coefficient in an otherwise homogeneous phantom while keeping the scattering coefficient same. The high frequency (100 MHz) modulated dual out-of-phase laser source light is propagated through the phantom. The interference of these sources creates an amplitude null and a phase shift of 180° along a plane between the two sources with a homogeneous object. A solid resin phantom with inhomogeneities simulating the tumor is used in our experiment. The amplitude and phase changes are found to be disturbed by the presence of the inhomogeneity in the object. The experimental data (amplitude and the phase measured at the detector) are used for reconstruction. The results show that the method is able to detect multiple inhomogeneities with sizes of 4 mm. The localization error for a 5 mm inhomogeneity is found to be approximately 1 mm.

Diffuse optical tomographic imager using a single light source

Near-infrared diffuse optical tomography (DOT) technique has the capability of providing good quantitative reconstruction of tissue absorption and scattering properties with additional inputs such as input and output modulation depths and correction for the photon leakage. We have calculated the two-dimensional (2D) input modulation depth from three-dimensional (3D) diffusion to model the 2D diffusion of photons. The photon leakage when light traverses from phantom to the fiber tip is estimated using a solid angle model. The experiments are carried for single (5 and 6 mm) as well as multiple inhomogeneities (6 and 8 mm) with higher absorption coefficient in a homogeneous phantom. Diffusion equation for photon transport is solved using finite element method and Jacobian is modeled for reconstructing the optical parameters. We study the development and performance of DOT system using modulated single light source and multiple detectors. The dual source methods are reported to have better reconstruction capabilities to resolve and localize single as well as multiple inhomogeneities because of its superior noise rejection capability. However, an experimental setup with dual sources is much more difficult to implement because of adjustment of two out of phase identical light probes symmetrically on either side of the detector during scanning time. Our work shows that with a relatively simpler system with a single source, the results are better in terms of resolution and localization. The experiments are carried out with 5 and 6 mm inhomogeneities separately and 6 and 8 mm inhomogeneities both together with absorption coefficient almost three times as that of the background. The results show that our experimental single source system with additional inputs such as 2D input/output modulation depth and air fiber interface correction is capable of detecting 5 and 6 mm inhomogeneities separately and can identify the size difference of multiple inhomogeneities such as 6 and 8 mm. The localization error is zero. The recovered absorption coefficient is 93% of inhomogeneity that we have embedded in experimental phantom.

Linearization and Reconstruction of Non-linear Diffuse Optical Tomographic Image

Diffuse optical tomography (DOT) is one of the ways to probe highly scattering media such as tissue using low-energy near infra-red light (NIR) to reconstruct a map of the optical property distribution. The interaction of the photons in biological tissue is a non-linear process and the phton transport through the tissue is modelled using diffusion theory. The inversion problem is often solved through iterative methods based on nonlinear optimization for the minimization of a data-model misfit function. The solution of the non-linear problem can be improved by modeling and optimizing the cost functional. The cost functional is f(x) = x(T)Ax - b(T)x + c and after minimization, the cost functional reduces to Ax = b. The spatial distribution of optical parameter can be obtained by solving the above equation iteratively for x. As the problem is non-linear, ill-posed and ill-conditioned, there will be an error or correction term for x at each iteration. A linearization strategy is proposed for the solution of the nonlinear ill-posed inverse problem by linear combination of system matrix and error in solution. By propagating the error (e) information (obtained from previous iteration) to the minimization function f(x), we can rewrite the minimization function as f(x; e) = (x + e)(T) A(x + e) - b(T)(x + e) + c. The revised cost functional is f(x; e) = f(x) + e(T)Ae. The self guided spatial weighted prior (e(T)Ae) error (e, error in estimating x) information along the principal nodes facilitates a well resolved dominant solution over the region of interest. The local minimization reduces the spreading of inclusion and removes the side lobes, thereby improving the contrast, localization and resolution of reconstructed image which has not been possible with conventional linear and regularization algorithm.

Flux density calibration in diffuse optical tomographic systems

The solution of the forward equation that models the transport of light through a highly scattering tissue material in diffuse optical tomography (DOT) using the finite element method gives flux density (Phi) at the nodal points of the mesh. The experimentally measured flux (U-measured) on the boundary over a finite surface area in a DOT system has to be corrected to account for the system transfer functions (R) of various building blocks of the measurement system. We present two methods to compensate for the perturbations caused by R and estimate true flux density (Phi) from U-measured(cal). In the first approach, the measurement data with a homogeneous phantom (U-measured(homo)) is used to calibrate the measurement system. The second scheme estimates the homogeneous phantom measurement using only the measurement from a heterogeneous phantom, thereby eliminating the necessity of a homogeneous phantom. This is done by statistically averaging the data (U-measured(hetero)) and redistributing it to the corresponding detector positions. The experiments carried out on tissue mimicking phantom with single and multiple inhomogeneities, human hand, and a pork tissue phantom demonstrate the robustness of the approach. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE) DOI: 10.1117/1.JBO.18.2.026023]