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Abstract. Visible-light optical coherence tomography (vis-OCT) is an emerging imaging modality, providing new capabilities in both anatomical and functional imaging of biological tissue. It relies on visible light illumination, whereas most commercial and investigational OCTs use near-infrared light. As a result, vis-OCT requires different considerations in engineering design and implementation but brings unique potential benefits to both fundamental research and clinical care of several diseases. Here, we intend to provide a summary of the development of vis-OCT and its demonstrated applications. We also provide perspectives on future technology improvement and applications.

Abstract:We achieved human retinal imaging using visible-light optical coherence tomography (vis-OCT) guided by an integrated scanning laser ophthalmoscopy (SLO). We adapted a spectral domain OCT configuration and used a supercontinuum laser as the illumating source. The center wavelength was 564 nm and the bandwidth was 115 nm, which provided a 0.97 µm axial resolution measured in air. We characterized the sensitivity to be 86 dB with 226 µW incidence power on the pupil. We also integrated an SLO that shared the same optical path of the vis-OCT sample arm for alignment purposes. We demonstrated the retinal imaging from both systems centered at the fovea and optic nerve head with 20° × 20° and 10° × 10° field of view. We observed similar anatomical structures in vis-OCT and NIR-OCT. The contrast appeared different from vis-OCT to NIR-OCT, including slightly weaker signal from intra-retinal layers, and increased visibility and contrast of anatomical layers in the outer retina.

With the advent of cloud computing, it has become increasingly popular for data owners to outsource their data to public cloud servers while allowing data users to retrieve this data. For privacy concerns, secure searches over encrypted cloud data has motivated several research works under the single owner model. However, most cloud servers in practice do not just serve one owner; instead, they support multiple owners to share the benefits brought by cloud computing. In this paper, we propose schemes to deal with Privacy preserving Ranked Multi-keyword Search in a Multi-owner model (PRMSM). To enable cloud servers to perform secure search without knowing the actual data of both keywords and trapdoors, we systematically construct a novel secure search protocol. To rank the search results and preserve the privacy of relevance scores between keywords and files, we propose a novel Additive Order and Privacy Preserving Function family. To prevent the attackers from eavesdropping secret keys and pretending to be legal data users submitting searches, we propose a novel dynamic secret key generation protocol and a new data user authentication protocol. Furthermore, PRMSM supports efficient data user revocation. Extensive experiments on real-world datasets confirm the efficacy and efficiency of PRMSM.

Abstract:We measured hemoglobin oxygen saturation (sO 2 ) in the retinal circulation in healthy humans using visible-light optical coherence tomography (vis-OCT). The measurements showed clear oxygenation differences between central retinal arteries and veins close to the optic nerve head. Spatial variations at different vascular branching levels were also revealed. In addition, we presented theoretical and experimental results to establish that noises in OCT intensity followed Rice distribution. We used this knowledge to retrieve unbiased estimation of true OCT intensity to improve the accuracy of vis-OCT oximetry, which had inherently lower signal-to-nose ratio from human eyes due to safety and comfort limitations. We demonstrated that the new statistical-fitting sampling strategy could reduce the estimation error in sO 2 by three percentage points (pp). The presented work aims to provide a foundation for using vis-OCT to achieve accurate retinal oximetry in clinical settings. G. Garhöfer, and L. Schmetterer, "Retinal oxygen metabolism during normoxia and hyperoxia in healthy subjects," Invest.

Face recognition has been a hot research area for its wide range of applications [1]. In human identification scenarios, facial metrics are more naturally accessible than many other biometrics, such as iris, fingerprint, and palm print [2]. Face recognition is also highly valuable in human computer interaction, access control, video surveillance, and many other applications. Although 2D face recognition research made significant progresses in recent years, its accuracy is still highly depended on light conditions and human poses [3, 4]. When the light is dim or the face poses are not properly aligned in the camera view, the recognition accuracy will suffer. The fast evolution of 3D sensors reveals a new path for face recognition that could overcome the fundamental limitations of 2D technologies. The geometric information contained in 3D facial data could substantially improve the recognition accuracy under conditions that are difficult for 2D technologies [5]. Many researchers have turned their focuses to 3D face recognition and made this research area a new trend. A general work flow for 3D face recognition is shown in Fig. 1. The work flow could be decomposed into two phases and five stages. In the training phase, 3D face data are acquired and then preprocessed to obtain "clean" 3D faces. Then the data are processed by feature extraction algorithms to find the features that could be used to differentiate faces. The features of each face are then stored into the feature database. In the testing phase, the target face goes through the acquisition, preprocessing, and feature extraction Abstract 3D face recognition has become a trending research direction in both industry and academia. It inherits advantages from traditional 2D face recognition, such as the natural recognition process and a wide range of applications. Moreover, 3D face recognition systems could accurately recognize human faces even under dim lights and with variant facial positions and expressions, in such conditions 2D face recognition systems would have immense difficulty to operate. This paper summarizes the history and the most recent progresses in 3D face recognition research domain. The frontier research results are introduced in three categories: pose-invariant recognition, expression-invariant recognition, and occlusion-invariant recognition. To promote future research, this paper collects information about publicly available 3D face databases. This paper also lists important open problems.

Abstract-This paper introduces a set of low-complexity algorithms that when coupled with link layer retransmission mechanisms, strengthen wireless communication security. Our basic idea is to generate a series of secrets from inevitable transmission errors and other random factors in wireless communications. Because these secrets are constantly extracted from the communication process in realtime, we call them dynamic secrets.Dynamic secrets have interesting security properties. They offer a complementary mechanism to existing security protocols. Even if the adversary exploits a vulnerability and steals the underlying system secret, security can be automatically replenished. In many scenarios, it is also possible to bootstrap a secure communication with the dynamic secrets.

Chronic cranial window (CCW) is an essential tool in enabling longitudinal imaging and manipulation of various brain activities in live animals. However, an active CCW capable of sensing the concealed in vivo environment while simultaneously providing longitudinal optical access to the brain is not currently available. Here we report a disposable ultrasound-sensing CCW (usCCW) featuring an integrated transparent nanophotonic ultrasonic detector fabricated using soft nanoimprint lithography process. We optimize the sensor design and the associated fabrication process to significantly improve detection sensitivity and reliability, which are critical for the intend longitudinal in vivo investigations. Surgically implanting the usCCW on the skull creates a self-contained environment, maintaining optical access while eliminating the need for external ultrasound coupling medium for photoacoustic imaging. Using this usCCW, we demonstrate photoacoustic microscopy of cortical vascular network in live mice over 28 days. This work establishes the foundation for integrating photoacoustic imaging with modern brain research.