Cien Fan
Biographic Data
| ID | 10017189 |
|---|---|
| NAME | Cien Fan |
| GIVEN NAMES | Cien |
| FAMILY NAME | Fan |
| SIGNATURE | FAN C |
| AFFILIATIONS | Wuhan University |
| ORCID | 0000-0002-4973-6444 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Symmetrical awareness network for cross-site ultrasound thyroid nodule segmentation
Recent years have seen remarkable progress of learning-based methods on Ultrasound Thyroid Nodules segmentation. However, with very limited annotations, the multi-site training data from different domains makes the task remain challenging. Due to domain shift, the existing methods cannot be well generalized to the out-of-set data, which limits the practical application of deep learning in the field of medical imaging. In this work, we propose an …
Automated Multi-View Multi-Modal Assessment of Covid-19 Patients Using Reciprocal Attention and Biomedical Transform
Automated severity assessment of coronavirus disease 2019 (COVID-19) patients can help rationally allocate medical resources and improve patients' survival rates. The existing methods conduct severity assessment tasks mainly on a unitary modal and single view, which is appropriate to exclude potential interactive information. To tackle the problem, in this paper, we propose a multi-view multi-modal model to automatically assess the severity of CO…
No prominent works on this page.
Automated Multi-View Multi-Modal Assessment of Covid-19 Patients Using Reciprocal Attention and Biomedical Transform
Automated severity assessment of coronavirus disease 2019 (COVID-19) patients can help rationally allocate medical resources and improve patients' survival rates. The existing methods conduct severity assessment tasks mainly on a unitary modal and single view, which is appropriate to exclude potential interactive information. To tackle the problem, in this paper, we propose a multi-view multi-modal model to automatically assess the severity of CO…
Symmetrical awareness network for cross-site ultrasound thyroid nodule segmentation
Recent years have seen remarkable progress of learning-based methods on Ultrasound Thyroid Nodules segmentation. However, with very limited annotations, the multi-site training data from different domains makes the task remain challenging. Due to domain shift, the existing methods cannot be well generalized to the out-of-set data, which limits the practical application of deep learning in the field of medical imaging. In this work, we propose an …
AI in cancer detection (2 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Artificial Intelligence in Healthcare and Education (1 work) · Artificial neural network (1 work) · Computer vision (1 work) · COVID-19 diagnosis using AI (1 work) · Data mining (1 work) · Deep learning (1 work) · Disease (1 work)