A5048883716- AI in cancer detection
- Advanced Neural Network Applications
- Traditional Chinese Medicine Studies
- Wireless Sensor Networks and IoT
- Artificial Intelligence in Healthcare
- Innovation in Digital Healthcare Systems
- Optimization and Packing Problems
- Safety and Risk Management
- Medical Image Segmentation Techniques
- Advanced Technologies in Various Fields
- Bone health and treatments
- Radiomics and Machine Learning in Medical Imaging
- Advanced Numerical Analysis Techniques
- Educational Technology and Assessment
- Healthcare Systems and Public Health
- Facility Location and Emergency Management
- Bone health and osteoporosis research
- Manufacturing Process and Optimization
- Industrial Technology and Control Systems
- Service-Oriented Architecture and Web Services
- Bone Metabolism and Diseases
- Advanced Image Fusion Techniques
- Internet of Things and Social Network Interactions
- Cognitive Computing and Networks
CRRC (China)
2024
Shenzhen Technology University
2022-2023
Shijiazhuang Tiedao University
2012
Institute of Information Engineering
2010-2011
In recent years, with the increasing incidence of cancer, regular physical examination is an important way to find cancer. Nuclear screening method for diagnosis gastrointestinal diseases, but it challenging in face small and fuzzy images. Different from traditional medical objects, pathological slice images are mostly blurry tiny, which somewhat difficult detect segment. The diagnostic lacks rapid quantitative analysis has a certain delay diagnosis, image processing uses morphological...
Abstract Medical diagnosis is the basis for modern medical treatment planning, rapid and accurate testing responsible patients’ lives health. Thanks to increasingly sophisticated large-scale data collection techniques, advantages of big artificial intelligence technologies analysis are gradually coming fore. However, mostly have missing items non-human biases, common algorithms often show instability in learning distribution patterns. In this paper, a feature interpolation algorithm based on...
The recognition of medical images, especially endoscopic ultrasound has the characteristics changing images and insignificant gray-scale changes, which requires repeated observation comparison by staff. In view above-mentioned imaging, a system scheme suitable for image processing is proposed, can analyze biliary tract, gallbladder, abdominal lymph nodes, liver, descending duodenum, duodenal bulb, stomach, pancreas, pancreatic there are total 10 ultrasonic organs, including 21 kinds...
The traditional emergency classification is lack of dynamic analysis in rescue and disaster incident management, it difficult to accurately quantify the providing practical guidance scientific issues. In this paper, Fuzzy AHP cluster researched, can effectively integrate expert consensus, meet requirements reflect emergencies.
This paper mainly introduces the methods and steps of book intelligent weeding in university libraries based on BP neural network. It conducts a research extraction used books features, network learning algorithm its improved algorithm, training sample processing, convergence other issues. Finally experimental results MATLAB simulation show that application BPNN model is feasible nd effective.
Placental volume is an important indicator for evaluating fetal health, and automatic identification of placenta calculation its great significance in clinical practice. Due to the complexity diversity placental images, domestic foreign scholars have proposed a variety image recognition segmentation methods. Among them, convolutional neural network method widely used, but this has black box theory, which difficult explain requires large number training samples. In context, paper proposes...