A5009777586- Retinal Imaging and Analysis
- Retinal Diseases and Treatments
- Retinal and Optic Conditions
- Remote-Sensing Image Classification
- Advanced Image Fusion Techniques
- Digital Imaging for Blood Diseases
- Glaucoma and retinal disorders
- Image and Signal Denoising Methods
- CNS Lymphoma Diagnosis and Treatment
- Atmospheric and Environmental Gas Dynamics
- Geological Studies and Exploration
- Infrared Target Detection Methodologies
- Acute Ischemic Stroke Management
- Sparse and Compressive Sensing Techniques
- Multimodal Machine Learning Applications
- Hydrocarbon exploration and reservoir analysis
Shantou University
2021-2025
Chinese University of Hong Kong
2021-2025
Nanjing University of Science and Technology
2023-2024
Shantou University Medical College
2023-2024
Geological Exploration Technology Institute of Jiangsu Province
2014
Macular hole (MH) and cystoid macular edema (CME) are two common retinal pathologies that cause vision loss. Accurate segmentation of MH CME in OCT images can greatly aid ophthalmologists to evaluate the relevant diseases. However, it is still challenging as complicated pathological features images, such diversity morphologies, low imaging contrast, blurred boundaries. In addition, lack pixel-level annotation data one important factors hinders further improvement accuracy. Focusing on these...
Vitreoretinal lymphoma (VRL) remains a diagnostic challenge due to its scarce prevalence, and delayed diagnosis usually results in blindness even fatal outcomes. Herein, an artificial intelligence (AI) system is developed identify VRL among 16 retinal diseases conditions on optical coherence tomography (OCT) images with the cross‐subject meta‐transfer learning (CS‐MTL) algorithm. Extensive experiments of few‐shot recognition tasks prove robustness our model 1‐, 3‐, 5‐shot scenarios,...
Reconstructing the 3D hyperspectral image (HSI) from 2D snapshot measurements is a key task in spectral compressive imaging (SCI). Traditional model-based HSI reconstruction methods rely on hand-crafted priors. Recently, deep unfolding networks (DUNs) learn priors using convolutional neural (CNNs) and have achieved satisfactory results. Most of DUNs assume degradations SCI are known. However, due to phase aberration distortion problems real process, there certain gap between ideal...
Abstract Objective. Neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV) present many similar clinical features. However, there are significant differences in the progression of nAMD PCV. it is crucial to make accurate diagnosis for treatment. In this paper, we propose a structure-radiomic fusion network (DRFNet) differentiate PCV optical coherence tomography (OCT) images. Approach. The subnetwork (RIMNet) designed automatically segment lesion...
Purpose: To develop an algorithm to detect and quantify hyperreflective dots (HRDs) on optical coherence tomography (OCT) in patients with diabetic macular edema (DME). Materials Methods: Twenty OCTs (each OCT contains 128 b scans) from 20 diagnosed DME were included this study. Two types of HRDs, hard exudates small HRDs (hypothesized be activated microglia), identified labeled independently by two raters. An using deep learning technology was developed based input (in total 2,560 manual...
Fusing low resolution (LR) hyperspectral image (HSI) with a high (HR) multispectral (MSI) could enhance the spatial and quality of HSI. Current deep learning (DL) HSI-MSI fusion networks have achieved encouraging results, but their performance relies on large number training images known degradations consistent testing data. The trained DL model may fail data unseen during inference. In this study, we propose multiple proximal network (MDPro-Net) for fusion, unknown spatial-spectral latent...
Purpose: To investigate the topographic characters of inter-individual variations macular choroidal thickness (CT). Methods: This was a retrospective study. Macular CT data for 900 0.2 × 0.2-mm grids from 410 healthy eyes were collected swept-source optical coherence tomography. Following analysis factors associated with mean CT, β-coefficients included in each grid summarized changes analysis. Additionally, coefficient variance (CoV), determination (CoD), and unexplained (CoVU) calculated...
Recently, the position of shale gas is more and important in world energy structure. The lithology Xiamaling Formation Beijing area mainly include siltstone, silty shale. organic carbon content relatively high, averaging 2.28%. kerogen type matter dominated by II 1 2 types, thermal evolution level 2.05%. Intergranular micropore well developed, most diameter 1-7µm, so reservoir condition good. brittle mineral it can be easily fractured production. clay has a good adsorption capacity. Through...
Optical coherence tomography (OCT) is widely used in the diagnosis of retinal diseases. Reading OCT images and summarizing its insights a routine, yet nonetheless time-consuming task. Automatic report generation can alleviate this issue. There are two major challenges task: (1) An image may contain several fundus abnormalities it difficult to detect them all simultaneously. (2) The diagnostic reports complex, which need describe multiple lesions. In paper, we propose deep learning-based...