arXiv subjects

Mengyao Yu

Publications and source records attributed to Mengyao Yu.

4 recordsLinked to original sources

arXiv2026

Mid-infrared Fourier ptychographic upconversion imaging

Frequency upconversion technique offers an appealing approach for sensitive mid-infrared (MIR) imaging at room temperature. However, the spatial resolution of the upconversion imager has been notoriously restricted by the limited transverse section of the involved nonlinear crystal at the Fourier plane. Here, we implement a wide-field and high-resolution MIR upconversion imaging system based on elliptical pumping and Fourier ptychography. Specifically, an elliptical pump beam is engineered to accommodate the narrow aperture of chirped-poling crystals, thus facilitating the acquisition of high spatial frequency components in the lateral direction. Such an elliptical passband in the Fourier space is then discretely rotated to generate a sequence of upconversion images, which allows computational recovery of a high-resolution object image through a combination of synthetic aperture and phase retrieval operations. Consequently, an enhanced spatial resolution of 39 $\mu$m is achieved within a field of view about 25 mm, which corresponds to a space-bandwidth product of 3.2$\times$10$^5$, over tenfold larger than previously demonstrated values. Moreover, the MIR upconversion imager can operate under a low-light illumination of 1 photon/pulse/pixel. Therefore, the presented paradigm of nonlinear Fourier ptychography paves the way toward high-throughput infrared imaging with massive resolvable elements and single-photon sensitivity, which would stimulate a variety of applications such as industry inspection and biomedical diagnosis.

physics.optics↗

arXiv2026

Wide-field mid-infrared edge-enhanced upconversion imaging

Edge-enhanced imaging is critical for visualizing weakly absorbing and transparent objects. Extending this functionality into the mid-infrared (MIR) region enables chemical sensitivity and improved imaging performance for biomedical, material, and remote-sensing applications. Here, we present a wide-field MIR edge-enhanced upconversion imaging system that integrates vortex-pump complex-amplitude engineering with aperiodic quasi-phase matching. In contrast to the bright-field modality, the wide-field edge-enhanced operation shows sensitive dependence on the crystal position relative to the Fourier plane. The system achieves single-shot operation with a 25-mm field of view and 79-$\mu$m spatial resolution, yielding a record-high space-bandwidth product of $7.9 \times 10^4$. We show that this capability enables direct visualization of phase gradients in transparent optical elements and enhances structural contrast in biological specimens. The demonstrated architecture combines high sensitivity, spectral specificity, and robust edge detection, offering a promising route toward advanced MIR imaging in industrial inspection and biomedical diagnostics.

physics.optics↗

arXiv2024

CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI

Cardiac magnetic resonance imaging (MRI) has emerged as a clinically gold-standard technique for diagnosing cardiac diseases, thanks to its ability to provide diverse information with multiple modalities and anatomical views. Accelerated cardiac MRI is highly expected to achieve time-efficient and patient-friendly imaging, and then advanced image reconstruction approaches are required to recover high-quality, clinically interpretable images from undersampled measurements. However, the lack of publicly available cardiac MRI k-space dataset in terms of both quantity and diversity has severely hindered substantial technological progress, particularly for data-driven artificial intelligence. Here, we provide a standardized, diverse, and high-quality CMRxRecon2024 dataset to facilitate the technical development, fair evaluation, and clinical transfer of cardiac MRI reconstruction approaches, towards promoting the universal frameworks that enable fast and robust reconstructions across different cardiac MRI protocols in clinical practice. To the best of our knowledge, the CMRxRecon2024 dataset is the largest and most protocal-diverse publicly available cardiac k-space dataset. It is acquired from 330 healthy volunteers, covering commonly used modalities, anatomical views, and acquisition trajectories in clinical cardiac MRI workflows. Besides, an open platform with tutorials, benchmarks, and data processing tools is provided to facilitate data usage, advanced method development, and fair performance evaluation.

eess.IV↗

arXiv2024

Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation

Most earlier 3D structure-based molecular generation approaches follow an atom-wise paradigm, incrementally adding atoms to a partially built molecular fragment within protein pockets. These methods, while effective in designing tightly bound ligands, often overlook other essential properties such as synthesizability. The fragment-wise generation paradigm offers a promising solution. However, a common challenge across both atom-wise and fragment-wise methods lies in their limited ability to co-design plausible chemical and geometrical structures, resulting in distorted conformations. In response to this challenge, we introduce the Deep Geometry Handling protocol, a more abstract design that extends the design focus beyond the model architecture. Through a comprehensive review of existing geometry-related models and their protocols, we propose a novel hybrid strategy, culminating in the development of FragGen - a geometry-reliable, fragment-wise molecular generation method. FragGen marks a significant leap forward in the quality of generated geometry and the synthesis accessibility of molecules. The efficacy of FragGen is further validated by its successful application in designing type II kinase inhibitors at the nanomolar level.

physics.chem-ph↗