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1. Smartphone videoscopy: Recent progress and opportunities for biosensing

   https://doi.org/10.1515/aot-2021-0009  

   Wang, Yan; Zhang, Shengwei; Wei, Qingshan (April 2021, Advanced Optical Technologies)

   Abstract Smartphone is emerging as a portable analytical biosensing platform in many point-of-care (POC) applications such as disease diagnostics, environmental monitoring, and food toxin screening. With the recent advancement of imaging technologies on the smartphone, the manual control of acquisition settings (e.g., exposure time, frame rate, focusing distance, etc.) has already been expanded from the photo to the video capturing mode. In modern smartphone models, high frame rate (above 100 fps) can be achieved to bring in a new temporal dimension to the smartphone-supported POC tests by recording high-definition videos. This opens up a new analytical method defined as smartphone videoscopy. In this review, the recent development of smartphone videoscopy is summarized based on different POC applications. Representative examples of smartphone videoscopy systems and how these time-dependent measurements could open up new opportunities for POC diagnostics are discussed in detail. The advances demonstrated so far illustrate the promising future of smartphone videoscopy in biosensing, POC diagnostics, and time-resolved analysis in general. 

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2. Regularized tomographic PIV for incompressible flows based on conservation of mass

   https://doi.org/10.1364/AO.380720  

   Liu, Ning; Ma, Lin (February 2020, Applied Optics)

   Three-dimensional and three-component (3D3C) velocity measurements have long been desired to resolve the 3D spatial structures of turbulent flows. Recent advancements have demonstrated tomographic particle image velocimetry (tomo-PIV) as a powerful technique to enable such measurements. The existing tomo-PIV technique obtains 3D3C velocity field by cross-correlating two frames of 3D tomographic reconstructions of the seeding particles. A most important issue in 3D3C velocity measurement involves uncertainty, as the derivatives of the measurements are usually of ultimate interest and uncertainties are amplified when calculating derivatives. To reduce the uncertainties of 3D3C velocity measurements, this work developed a regularized tomo-PIV method. The new method was demonstrated to enhance accuracy significantly by incorporating the conservation of mass into the tomo-PIV process. The new method was demonstrated and validated both experimentally and numerically. The results illustrated that the new method was able to enhance the accuracy of 3D3C velocity measurements by 40%–50% in terms of velocity magnitude and by 0.6°–1.1° in terms of velocity orientation, compared to the existing tomo-PIV technique. These improvements brought about by the new method are expected to expand the application of tomo-PIV techniques when accuracy and quantitative 3D flow properties are required. 

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3. 3D object tracking using integral imaging with mutual information and Bayesian optimization

   https://doi.org/10.1364/OE.517312  

   Wani, Pranav; Usmani, Kashif; Krishnan, Gokul; Javidi, Bahram (February 2024, Optics Express)

   Integral imaging has proven useful for three-dimensional (3D) object visualization in adverse environmental conditions such as partial occlusion and low light. This paper considers the problem of 3D object tracking. Two-dimensional (2D) object tracking within a scene is an active research area. Several recent algorithms use object detection methods to obtain 2D bounding boxes around objects of interest in each frame. Then, one bounding box can be selected out of many for each object of interest using motion prediction algorithms. Many of these algorithms rely on images obtained using traditional 2D imaging systems. A growing literature demonstrates the advantage of using 3D integral imaging instead of traditional 2D imaging for object detection and visualization in adverse environmental conditions. Integral imaging’s depth sectioning ability has also proven beneficial for object detection and visualization. Integral imaging captures an object’s depth in addition to its 2D spatial position in each frame. A recent study uses integral imaging for the 3D reconstruction of the scene for object classification and utilizes the mutual information between the object’s bounding box in this 3D reconstructed scene and the 2D central perspective to achieve passive depth estimation. We build over this method by using Bayesian optimization to track the object’s depth in as few 3D reconstructions as possible. We study the performance of our approach on laboratory scenes with occluded objects moving in 3D and show that the proposed approach outperforms 2D object tracking. In our experimental setup, mutual information-based depth estimation with Bayesian optimization achieves depth tracking with as few as two 3D reconstructions per frame which corresponds to the theoretical minimum number of 3D reconstructions required for depth estimation. To the best of our knowledge, this is the first report on 3D object tracking using the proposed approach. 

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4. A Mechanism Design Approach to Vendor Managed Inventory

   https://doi.org/10.1287/mnsc.2019.3297  

   Kadiyala, Bharadwaj; Özer, Özalp; Bensoussan, Alain (October 2019, Management Science)

   This paper studies an inventory management problem faced by an upstream supplier that is in a collaborative agreement, such as vendor-managed inventory (VMI), with a retailer. A VMI partnership provides the supplier an opportunity to manage in- ventory for the supply chain in exchange for point-of-sales (POS)- and inventory-level information from the retailer. However, retailers typically possess superior local market information and as has been the case in recent years, are able to capture and analyze customer purchasing behavior beyond the traditional POS data. Such analyses provide the retailer access to market signals that are otherwise hard to capture using POS information. We show and quantify the implication of the financial obligations of each party in VMI that renders communication of such important market signals as noncredible. To help insti- tute a sound VMI collaboration, we propose learn and screen—a dynamic inventory mechanism—for the supplier to effectively manage inventory and information in the supply chain. The proposed mechanism combines the ability of the supplier to learn about market conditions from POS data (over multiple selling periods) and dynamically de- termine when to screen the retailer and acquire his private demand information. Inventory decisions in the proposed mechanism serve a strategic purpose in addition to their classic role of satisfying customer demand. We show that our proposed dynamic mechanism significantly improves the supplier’s expected profit and increases the efficiency of the overall supply chain operations under a VMI agreement. In addition, we determine the market conditions in which a strategic approach to VMI results in significant profit im- provements for both firms, particularly when the retailer has high market power (i.e., when the supplier highly depends on the retailer) and when the supplier has relatively less knowledge about the end customer/market compared with the retailer. 

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5. Optimizing dual‐energy CT technique for iodine‐based contrast‐to‐noise ratio, a theoretical study

   https://doi.org/10.1002/mp.17010  

   Terzioglu, Fatma; Sidky, Emil Y; Phillips, John Paul; Reiser, Ingrid S; Bal, Guillaume; Pan, Xiaochuan (April 2024, Medical Physics)

   Abstract BackgroundDual‐energy CT (DECT) systems provide valuable material‐specific information by simultaneously acquiring two spectral measurements, resulting in superior image quality and contrast‐to‐noise ratio (CNR) while reducing radiation exposure and contrast agent usage. The selection of DECT scan parameters, including x‐ray tube settings and fluence, is critical for the stability of the reconstruction process and hence the overall image quality. PurposeThe goal of this study is to propose a systematic theoretical method for determining the optimal DECT parameters for minimal noise and maximum CNR in virtual monochromatic images (VMIs) for fixed subject size and total radiation dose. MethodsThe noise propagation in the process of projection based material estimation from DECT measurements is analyzed. The main components of the study are the mean pixel variances for the sinogram and monochromatic image and the CNR, which were shown to depend on the Jacobian matrix of the sinograms‐to‐DECT measurements map.Analytic estimates for the mean sinogram and monochromatic image pixel variances and the CNR as functions of tube potentials, fluence, and VMI energy are derived, and then used in a virtual phantom experiment as an objective function for optimizing the tube settings and VMI energy to minimize the image noise and maximize the CNR. ResultsIt was shown that DECT measurements corresponding to kV settings that maximize the square of Jacobian determinant values over a domain of interest lead to improved stability of basis material reconstructions.Instances of non‐uniqueness in DECT were addressed, focusing on scenarios where the Jacobian determinant becomes zero within the domain of interest despite significant spectral separation. The presence of non‐uniqueness can lead to singular solutions during the inversion of sinograms‐to‐DECT measurements, underscoring the importance of considering uniqueness properties in parameter selection.Additionally, the optimal VMI energy and tube potentials for maximal CNR was determined. When the x‐ray beam filter material was fixed at 2 mm of aluminum and the photon fluence for low and high kV scans were considered equal, the tube potential pair of 60/120 kV led to the maximal iodine CNR in the VMI at 53 keV. ConclusionsOptimizing DECT scan parameters to maximize the CNR can be done in a systematic way. Also, choosing the parameters that maximize the Jacobian determinant over the set of expected line integrals leads to more stable reconstructions due to the reduced amplification of the measurement noise. Since the values of the Jacobian determinant depend strongly on the imaging task, careful consideration of all of the relevant factors is needed when implementing the proposed framework. 

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