Jia-Qi Lü

The high-precision estimation of spatial parameters, such as transverse displacement, beam tilt and angular rotation, is of great importance in precision measurement, optical imaging and quantum sensing. Structured light, with controllable spatial modes and special momentum degrees of freedom, provides new opportunities to promote the encoding and readout of quantum metrology for spatial parameters. Here, we review recent progress in structured-light-enabled quantum metrology for spatial parameter estimation. The theoretical foundations of parameter estimation are introduced, based on which the modal-encoding mechanisms of higher-order structured light modes in spatial parameter measurements are summarized. Representative studies in which structured light is combined with nonclassical resources and the mode-matched readout strategies to achieve quantum enhancement are also demonstrated. In addition, current technical bottlenecks and future directions are discussed.

Tissue expanders are widely used for organ and tissue reconstruction surgery. Hydrogel tissue expanders that swell in a biofluid are promising for minimally invasive operations. Nevertheless, clinical applications of existing hydrogel tissue expanders exhibit simple geometries, rapid swelling and insufficient mechanical performances. Here we develop a negatively charged polyelectrolyte hydrogel ink for light-based printing and prolonged yet large expansive profiles for surface organ and tissue reconstruction. This 4D-printed hydrogel tissue expander can be moulded in architecturally sophisticated constructs that adapt to the environment and show favourable mechanics without the need of external triggers for expansion. The ionization degree of the polyelectrolyte hydrogels is tunable by pH value in the surrounding medium and allows a volume equilibrium-swelling up to 10-30 times. In a rabbit model, we use the tissue expander for reconstruction of human-size ears and breasts, highlighting their multifold advantages over existing clinically adopted methods and thus future translation potentials.

As one of the 3D printing technologies, digital light processing (DLP) 3D printing technology has been widely applied in biomedical engineering. The principles and advantages of DLP 3D printing technology are compared with other 3D printing technologies, while the characteristics and applicable fields of each technique are analyzed. The applications of DLP 3D printing technology in tissue engineering, medical devices and pharmaceutical field are classified and summarized. Besides, the prospects and challenges of DLP 3D printing technology in biomedical engineering are discussed. With continuous advancement, DLP 3D printing technology will play an increasingly important role in personalized medicine and regenerative medicine.

The Airy beam has attracted great attention since it was proposed in 2007 due to its novel properties, such as non-diffraction, self-healing, and self-acceleration. However, the spin angular momentum (SAM), which is an intrinsic nature of light, has rarely been studied by the Airy beam. Here, we propose a kind of binary circular Airy beam (BCAB) with space-variant polarizations and vortex phases and study the SAM evolution of the BCAB during propagation. We find the effects of appearance and annihilation of SAM during the propagation of BCAB, and the SAM can be further manipulated by adjusting the initial phase and polarization distribution of BCAB. Moreover, the optical tube, optical needle, and optical cage carrying different SAMs are achieved in propagation, which can be applied in various regions, such as optical trapping and manipulation. The BCAB significantly enriches the family of structured light and provides a flexible control scheme of SAM, which can further promote the application of SAM in many fields.

High-order vortex beams carrying orbital angular momentum in the visible wavelength range are of tremendous interest for a diversity of applications, including super-resolution imaging, microfabrication, and underwater communications. Such beams can be generated directly from compact solid-state lasers; however, they generally have low topological charge number. In this work, we demonstrate the generation of high-order Laguerre–Gaussian (LG) modes from a simple Pr:YLF laser cavity and demonstrate its application in the measurement of angular velocity. We utilize enhanced intracavity spherical aberration to generate LG0,±m modes with m selectable up to 34, directly from a Pr:YLF laser operating at 640 nm. We utilize this laser beam in an off-axis illumination geometry in conjunction with the rotational Doppler effect, to measure the angular velocity of a spinning object. The demonstration highlights a potential application for these types of vortex laser.

Based on the longitudinal manipulation of polarization, a special vector optical beam (VOB) with customized polarization variation in propagation direction can be generated, whose properties and applications remain to be studied. Here, the self-healing propagation behaviors of the longitudinally varying VOB after an opaque object are investigated, and the localized polarization responses on the object distance are revealed. On this basis, characteristic parameters are defined to measure the distance of object, achieving a minimum relative error of 0.63% in a longitudinal range of 300 mm. Besides, the correlations and uncoupling methods of object distance and size are discussed. Our studies open new ways to use the structural properties of VOB and may be instructive for laser measurement.

Colorectal cancer (CRC) is one of the most common cancers worldwide. Early detection and removal of colorectal polyps during colonoscopy are crucial for preventing such cancers. With the development of artificial intelligence (AI) technology, it has become possible to detect and localize colorectal polyps in real time during colonoscopy using computer-aided diagnosis (CAD). This provides a reliable endoscopist reference and leads to more accurate diagnosis and treatment. This paper reviews AI-based algorithms for real-time detection of colorectal polyps, with a particular focus on the development of deep learning algorithms aimed at optimizing both efficiency and correctness. Furthermore, the challenges and prospects of AI-based colorectal polyp detection are discussed.