A5056744049- Biometric Identification and Security
- Face and Expression Recognition
- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Image Enhancement Techniques
- Fault Detection and Control Systems
- Medical Imaging Techniques and Applications
- Advanced Image Processing Techniques
- Medical Image Segmentation Techniques
- Digital Imaging for Blood Diseases
- Wood and Agarwood Research
- Image and Signal Denoising Methods
- Advanced X-ray and CT Imaging
- Advanced Steganography and Watermarking Techniques
- Gastric Cancer Management and Outcomes
- Human Pose and Action Recognition
- EEG and Brain-Computer Interfaces
- Anomaly Detection Techniques and Applications
- Color Science and Applications
- Domain Adaptation and Few-Shot Learning
- Multimodal Machine Learning Applications
- Security in Wireless Sensor Networks
- Lung Cancer Research Studies
- 2D Materials and Applications
- Stock Market Forecasting Methods
Chongqing Cancer Hospital
2019-2024
Chongqing University
2006-2023
Shenzhen University
2017-2022
Hubei Cancer Hospital
2022
Huazhong University of Science and Technology
2022
The Affiliated Yongchuan Hospital of Chongqing Medical University
2021
Chongqing Three Gorges Central Hospital
2021
Chongqing Medical University
2021
Shenzhen University Health Science Center
2020
University of California, Los Angeles
2018
Histopathological image analysis is an important technique for early diagnosis and detection of breast cancer in clinical practice. However, it has limited efficiency thus the still open issue medical analysis. To improve diagnostic accuracy reduce workload doctors, we devise a classification framework based on histology images by combining deep learning with machine methodologies this paper. Specifically, multi-network feature extraction model using pre-trained convolution neural networks...
Various imaging techniques combined with machine learning (ML) models have been used to build computer-aided diagnosis (CAD) systems for breast cancer (BC) detection and classification. The rise of deep in recent years, represented by convolutional neural network (CNN) models, has pushed the accuracy ML-based CAD a new level that is comparable human experts. Existing studies explored usage wide spectrum CNN BC detection, supervised mainstream. In this study, we propose semi-supervised...
For model-based state of charge (SOC) estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing error to increase. Constantly updating during operation, also known as online parameter identification, can effectively solve this problem. In paper, a lithium-ion is modeled using Thevenin model. A variable forgetting factor (VFF) strategy introduced improve recursive least squares (FFRLS) (VFF-RLS). novel method based on VFF-RLS for identification...
Efficient and realistic large-scale scene modeling is an important application of low-altitude remote sensing. Although the emerging 3DGS technology offers a simple process results, its high computational resource demands hinder direct in 3D reconstruction. To address this, this paper proposes novel grid-based segmentation technique Sparse point clouds, acting as indirect input for 3DGS, are first processed by Z-Score percentile-based filter to prepare pure segmentation. Then, through grid...
This paper proposes a variational model with barriers for Retinex, borrowing the ideas of barrier methods. We first present an energy functional and then deduce new from it by adding two barriers. The proposed is defined as constrained optimization problem associated deduced functional. Next, alternating minimization scheme used to solve model. Some theoretic analyses are given algorithm. Finally, numerical examples presented show effectiveness its
BACKGROUND Lung cancer is the most common cause of cancer-associated deaths worldwide. This study aimed to investigate efficacy and safety Traditional Chinese Medicine combining EGFR-TKIs in treatment NSCLC patients harboring EGFR mutations. MATERIAL AND METHODS involved 153 advanced-stage Patients were divided into a Control group (administered EGFR-TKI, n=61) an Experimental TKI, n=92). Progression-free survival (PFS) was evaluated for exon 19 deletion and/or 21 patients. Disease control...
Recently, deep-learning based methods have been widely used for computed tomography (CT) reconstruction. However, most of these need extra steps to convert the sinogrmas into CT images and so their networks are not end-to-end. In this paper, we propose an end-to-end deep network image reconstruction, which directly maps sparse sinogramss images. Our has three cascaded blocks, where first block is denoise interpolate sinograms, second map sinograms last The our implements filter...
In this paper, we present a fast and effective method for solving the Poisson-modified total variation model proposed in [9]. The existence uniqueness of are again proved using different method. A semi-implicit difference scheme is designed to discretize derived gradient descent flow with large time step can guarantee restored image be strictly positive domain. Experimental results show efficiency effectiveness our
Systematic molecular dynamics simulations, along with dielectric measurements on poly(vinyl methyl ether)/polystyrene blends, are performed to investigate the topological effect effective local concentration ϕeff and segmental in linear–linear (LLB), ring–ring (RRB), linear–ring (LRB) miscible blends. Compared LLB, a larger average value broader distribution of found RRB, which is attributed chain-bending-back from ring closure. In LRB, however, for components converge their linear blend...
Clinical case reports (CCRs) are a valuable means of sharing observations and insights in medicine. The form these documents varies, their content includes descriptions numerous, novel disease presentations treatments. Thus far, the text data within CCRs is largely unstructured, requiring significant human computational effort to render useful for in-depth analysis. In this protocol, we describe methods identifying metadata corresponding specific biomedical concepts frequently observed CCRs....
A fingerprint classification algorithm is proposed in this paper. It based on the features extracted from directional field of image. To improve accuracy field, an efficient estimation approach developed. Based improved singular points and relative are to generate input classifier. After encoding features, a fuzzy wavelet neural network-based classifier applied classify fingerprints for five-class problem. Experimental results show excellent performance
Minutiae pattern remains a widely used representation of fingerprint. The research on minutiae matching never stops due to its complexity and intractability. In this paper, an efficient fingerprint algorithm is proposed. To obtain reliable reference pairs, the bank coordinate systems introduced. derived from original features applied get more useful information about minutiae. improve accuracy matching, global optimum alignment approach developed, which targeted set pairs. Experimental...
Alzheimer's disease (AD) is a common irreversible neurodegenerative among elderlies. To identify the early stage of AD (i.e., mild cognitive impairment, MCI), many recent studies in literature use only single time point and ignore conducive multi-time points information. Therefore, we propose novel method that combines sparse smooth network with long short-term memory (LSTM) to late MCIs from resting-state functional magnetic resonance imaging (rs-fMRI). Specifically, first construct brain...