A5101401322- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Ultrasound and Hyperthermia Applications
- Cancer Research and Treatments
- Digital Imaging for Blood Diseases
- Virus-based gene therapy research
- Medical Image Segmentation Techniques
- Ovarian function and disorders
- Domain Adaptation and Few-Shot Learning
- Reproductive Biology and Fertility
- Reproductive Health and Contraception
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Assisted Reproductive Technology and Twin Pregnancy
- Advanced Image Fusion Techniques
- Reproductive System and Pregnancy
- Viral gastroenteritis research and epidemiology
- Cancer, Hypoxia, and Metabolism
Shenzhen Second People's Hospital
2005-2022
Guangdong Medical College
2022
Anhui Medical University
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...
Mitotic count is an important indicator for assessing the invasiveness of breast cancers. Currently, number mitoses manually counted by pathologists, which both tedious and time-consuming. To address this situation, we propose a fast accurate method to automatically detect mitosis from histopathological images. The proposed can identify mitotic candidates histological sections screening. Specifically, our exploits deep convolutional neural networks extract high-level features candidates....