Efficient boundary-guided scanning for high-resolution X-ray ptychography.

In the realm of X-ray ptychography experiments, a considerable amount of ptychography scans are typically performed within a field of view encompassing the target sample. While it is crucial to obtain overlapping scans in small increments over the region of interest for achieving high-resolution sample reconstruction, a significant number of these scans often redundantly measure the empty background within the wide field of view. To address this inefficiency, an innovative algorithm is proposed that introduces automatic guidance for data acquisition. The algorithm first directs the scan point to actively search for the object of interest within the field of view. Subsequently, it intelligently scans along the perimeter of the sample, strategically acquiring measurements exclusively within the boundary of the region of interest. By employing this approach, a reduction in the number of measurements required to obtain high-resolution reconstruction images is demonstrated, as compared with conventional raster scanning methods. Furthermore, the automatic guidance provided by the algorithm offers the added advantage of saving valuable time during the reconstruction process. Through practical implementation on real experiments, these findings showcase the efficacy of the proposed algorithm in enhancing the efficiency and accuracy of X-ray ptychography experiments. This novel approach holds immense potential for advancing sample analysis and imaging techniques in various scientific disciplines.

Determining optical material parameters with motion in structured illumination.

A set of power measurements as a function of controlled nanopositioner movement of a planar film arrangement in a standing wave field is presented as a means to obtain the thicknesses and the dielectric constants to a precision dictated by noise in an exciting laser beam and the positioning and detector process, all of which can be refined with averaging. From a mutual information perspective, knowing the set of positions at which measurements are performed adds information. While applicable to any arrangement of planar films, the implementation considered involves thin transmissive membranes, as are employed in applications such as optomechanics. We show that measured power data as a function of object position provides sensitivity to the film refractive index and far-subwavelength thickness. Use of a cost function allows iterative retrieval of the film parameters, and a multi-resolution framework is described as a computationally efficient procedure. The approach is complementary to ellipsometry and could play an important role in routine film characterization studies for fields involving solid state material processing, as is common in the semiconductor device field.

Printed optics: phantoms for quantitative deep tissue fluorescence imaging: publisher's note.

This note points out a number of corrections that were omitted from the published version of the article [Opt. Lett.41, 5230 (2016)OPLEDP0146-959210.1364/OL.41.005230].

Printed optics: phantoms for quantitative deep tissue fluorescence imaging.

Three-dimensional (3D) printing allows for complex or physiologically realistic phantoms, useful, for example, in developing biomedical imaging methods and for calibrating measured data. However, available 3D printing materials provide a limited range of static optical properties. We overcome this limitation with a new method using stereolithography that allows tuning of the printed phantom's optical properties to match that of target tissues, accomplished by printing a mixture of polystyrene microspheres and clear photopolymer resin. We show that Mie theory can be used to design the optical properties, and demonstrate the method by fabricating a mouse phantom and imaging it using fluorescence optical diffusion tomography.

Fabrication and application of heterogeneous printed mouse phantoms for whole animal optical imaging.

This work demonstrates the usefulness of 3D printing for optical imaging applications. Progress in developing optical imaging for biomedical applications requires customizable and often complex objects for testing and evaluation. There is therefore high demand for what have become known as tissue-simulating "phantoms." We present a new optical phantom fabricated using inexpensive 3D printing methods with multiple materials, allowing for the placement of complex inhomogeneities in complex or anatomically realistic geometries, as opposed to previous phantoms, which were limited to simple shapes formed by molds or machining. We use diffuse optical imaging to reconstruct optical parameters in 3D space within a printed mouse to show the applicability of the phantoms for developing whole animal optical imaging methods. This phantom fabrication approach is versatile, can be applied to optical imaging methods besides diffusive imaging, and can be used in the calibration of live animal imaging data.

Prediction of electric field frequency correlations for randomly scattering slabs in the nondiffusive regime with the scalar Bethe-Salpeter equation.

We show that a scalar Bethe-Salpeter equation model captures the measured copolarized electric field frequency correlation magnitude for randomly scattering slabs in the weakly scattering, nondiffusive regime. Consequently, the model could be used to form images of tissue on the millimeter and submillimeter length scale, and for environmental sensing with comparable scatter, as dictated by the optical scattering length in relation to the scattering domain size.

Unsupervised classification for region of interest in X-ray ptychography.

X-ray ptychography offers high-resolution imaging of large areas at a high computational cost due to the large volume of data provided. To address the cost issue, we propose a physics-informed unsupervised classification algorithm that is performed prior to reconstruction and removes data outside the region of interest (RoI) based on the multimodal features present in the diffraction patterns. The preprocessing time for the proposed method is inconsequential in contrast to the resource-intensive reconstruction process, leading to an impressive reduction in the data workload to a mere 20% of the initial dataset. This capability consequently reduces computational time dramatically while preserving reconstruction quality. Through further segmentation of the diffraction patterns, our proposed approach can also detect features that are smaller than beam size and correctly classify them as within the RoI.

Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence.

A super-resolution optical imaging method is presented that relies on the distinct temporal information associated with each fluorescent optical reporter to determine its spatial position to high precision with measurements of heavily scattered light. This multiple-emitter localization approach uses a diffusion equation forward model in a cost function, and has the potential to achieve micron-scale spatial resolution through centimeters of tissue. Utilizing some degree of temporal separation for the reporter emissions, position and emission strength are determined using a computationally efficient time stripping multiresolution algorithm. The approach circumvents the spatial resolution challenges faced by earlier optical imaging approaches using a diffusion equation forward model, and is promising for in vivo applications. For example, in principle, the method could be used to localize individual neurons firing throughout a rodent brain, enabling direct imaging of neural network activity.