Abstract
Ultrasound imaging is widely used for its non-invasiveness, portability, and cost-effectiveness. However, mastering freehand ultrasound requires years of training, contributing to a global shortage of skilled sonographers and delays in medical diagnoses. AI offers a promising solution to bridge this expertise gap, improving ultrasound accessibility across diverse clinical and remote settings. In this talk, I will explore how AI can simplify sonography from two perspectives: during examinations, by providing real-time 3D spatial and language-guided assistance, and after examinations, by automatically summarizing key findings to enhance diagnostic efficiency, accuracy, and workflow.
| Original language | English |
|---|---|
| Publication status | Published - 4 Mar 2025 |
| Event | HKBU-NVIDIA Joint Symposium 2025: HEALTH-TECH - Hong Kong Baptist University, Hong Kong, China Duration: 4 Mar 2025 → 4 Mar 2025 https://www.comp.hkbu.edu.hk/hkbu-nvidia-sym2025/#schedule (Link to conference schedule) |
Symposium
| Symposium | HKBU-NVIDIA Joint Symposium 2025 |
|---|---|
| Country/Territory | Hong Kong, China |
| Period | 4/03/25 → 4/03/25 |
| Internet address |
|
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Fingerprint
Dive into the research topics of 'Learning to Simplify Sonography during and after the Ultrasound Examination'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver