Artificial Intelligence-aimed Point-of-care Ultrasound Image Interpretation System
Recruiting now · Not applicable
Conditions studied: Ultrasound Image Interpretation
In brief
This proposal is for an one-year project. In this project, we aim to investigate the feasibility of using AI for sonographic image interpretation. The main project is responsible for coordination between the two sub-projects and the main project, providing image resources, and using U-Net (Convolutional Networks for Biomedical Image Segmentation) and Transfer Learning to build up the models for image recognition and validating the efficacy of the models. The purpose of Subproject 1 is to develop an image recognition system for dynamic images: pericardial effusion. After building up the model, validating the efficacy and future revision will be done. Subproject 2 comes out an image recognition system for static images: hydronephrosis. After building up the model, validating the efficacy and future revision will be done.
Key facts
- Study ID
- NCT04876157
- Run by
- National Taiwan University Hospital
- People needed
- 300
- Starts
- 2020-08-01
- Expected to finish
- 2026-12-31
- Last updated by the study team
- 2025-09-19
Who can join
Age: 20 and older. Sex: any. Healthy volunteers: not accepted.
You may qualify if…
- patients receiving echocardiography or renal ultrasound
You may not qualify if…
- patients not receiving echocardiography or renal ultrasound
Where it is running
- Wan-Ching Lien — Taipei, None Selected, Taiwan (enrolling)
Full record on ClinicalTrials.gov
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