A5060620393- Spectroscopy Techniques in Biomedical and Chemical Research
- Liver Disease Diagnosis and Treatment
- Digital Imaging for Blood Diseases
- Remote-Sensing Image Classification
- Systemic Sclerosis and Related Diseases
- Big Data and Business Intelligence
- Advanced Image Fusion Techniques
- Impact of AI and Big Data on Business and Society
- Surgical Simulation and Training
- Advanced Vision and Imaging
- Brain Tumor Detection and Classification
- Remote Sensing in Agriculture
- Augmented Reality Applications
- Soft Robotics and Applications
- Optical measurement and interference techniques
- Ocean Waves and Remote Sensing
- Ionosphere and magnetosphere dynamics
- Radar Systems and Signal Processing
- Advanced Sensor and Energy Harvesting Materials
- Digital Transformation in Industry
- Minimally Invasive Surgical Techniques
- Image Processing Techniques and Applications
- Robot Manipulation and Learning
- Advanced Data Processing Techniques
Tsinghua University
2021-2025
Guangxi Open University
2024
Baise University
2024
Longdong University
2021
Beijing University of Chemical Technology
2018-2020
To solve the problem of supervised convolutional neural network (CNN) models suffering from limited samples, a two-channel CNN is developed for medical hyperspectral images (MHSI) classification tasks. In proposed network, one channel end-to-end denoted as EtoE-Net, designed to realize unsupervised learning, obtaining representative and global fused features with fewer noises, by building pixel-by-pixel mapping between two source data, i.e., original MHSI data its principal component. On...
During minimally invasive surgery (MIS), three-dimensional (3D) endoscopes provide valuable 3D perception of the patient's internal structures. However, due to requirement two cameras and a relatively large baseline distance, imaging front-end conventional binocular (CB3D) endoscope usually lacks compactness. We aim develop novel compact monocular dual-view (MDV3D) system. optical design for MDV3D that exploits dichroic prism's reflection capability its light realize imaging, ensuring...
Currently, how to efficiently exploit useful information from multi-source remote sensing data for better Earth observation becomes an interesting but challenging problem. In this paper, we propose collaborative classification framework hyperspectral image (HSI) and Light Detection Ranging (LIDAR) via image-to-image convolutional neural network (CNN). There is mapping, learning a representation input source (i.e., HSI) output LIDAR). Then, the extracted features are expected own...
Abstract Background Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic (IMN) and hepatitis B virus-related (HBV-MN). However, the morphologic differences are not visible under light microscope certain renal biopsy tissues. Methods We propose here a deep learning-based framework for processing hyperspectral images of tissue to define difference between IMN HBV-MN based on component their immune complex deposition. Results The proposed can achieve an...
Abstract Background： Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic (IMN) and hepatitis B virus-related (HBV-MN). However, some cases, the morphologic differences are not visible under light microscope renal biopsy tissue. Methods： We proposed a deep learning-based framework for processing hyperspectral images of tissue to define difference between IMN HBV-MN based on component their immune complex deposition. Results: The can achieve an overall...
Abstract Background Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic (IMN) and hepatitis B virus-related (HBV-MN). However, some cases, the morphologic differences are not visible under light microscope renal biopsy tissue. Methods We proposed a deep learning-based framework for processing hyperspectral images of tissue to define difference between IMN HBV-MN based on component their immune complex deposition. Results The can achieve an overall...
Abstract Background: Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic (IMN) and hepatitis B virus-related (HBV-MN). However, the morphologic differences are not visible under light microscope certain renal biopsy tissues. Methods: We propose here a deep learning-based framework for processing hyperspectral images of tissue to define difference between IMN HBV-MN based on component their immune complex deposition. Results: The proposed can achieve...