A5012205185- AI in cancer detection
- Advanced Image Fusion Techniques
- Digital Radiography and Breast Imaging
- RNA regulation and disease
- Medical Image Segmentation Techniques
- COVID-19 diagnosis using AI
- Brain Tumor Detection and Classification
- Radiomics and Machine Learning in Medical Imaging
- Lung Cancer Diagnosis and Treatment
Sun Yat-sen University
2018-2022
Synthetic digital mammography (SDM), a 2D image generated from breast tomosynthesis (DBT), is used as potential substitute for full-field (FFDM) in clinic to reduce the radiation dose cancer screening. Previous studies exploited projection geometry and fused data DBT volume, with different post-processing techniques applied on re-projection which may generate appearance compared FFDM. To alleviate this issue, one possible solution an SDM using learning-based method model transformation...
Abstract The coronavirus disease 2019 (COVID-19) has infected more than 9.3 million people and caused over 0.47 deaths worldwide as of June 24, 2020. Chest imaging techniques including computed tomography X-ray scans are indispensable tools in COVID-19 diagnosis its management. strong infectiousness this brings a huge burden for radiologists. In order to overcome the difficulty improve accuracy diagnosis, artificial intelligence (AI)-based analysis methods explored. This survey focuses on...
Synthetic digital mammogram (SDM) is a 2D image generated from breast tomosynthesis (DBT) and used as substitute for full-field (FFDM) to reduce the radiation dose cancer screening. The previous deep learning-based method FFDM images ground truth, trained single neural network directly generate SDM with similar appearances (e.g., intensity distribution, textures) images. However, has different texture pattern DBT. difference in might make training of unstable result high-intensity...