SenseCare: a research platform for medical image informatics and interactive 3D visualization
SenseCare provides a range of AI toolkits for different tasks, including image segmentation, registration, lesion and landmark detection from various image modalities ranging from radiology to pathology. It also facilitates the data annotation and model training processes, which makes it easier for clinical researchers to develop and deploy customized AI models. In addition, it is clinic-oriented and supports various clinical applications such as diagnosis and surgical planning for lung cancer, liver tumor, coronary artery disease, etc. By simplifying AI-based medical image analysis, SenseCare has a potential to promote clinical research in a wide range of disease diagnosis and treatment applications.
Authors
- Qi Duan (ORCID: https://orcid.org/0000-0002-2407-6611)
- Shaoting Zhang (ORCID: https://orcid.org/0000-0002-8719-448X)
- Guotai Wang
- Shen Tian (ORCID: https://orcid.org/0000-0002-2839-6911)
Institutions
- University of Electronic Science and Technology of China (CN)
- Group Sense (China) (CN)
Publication Details
- Journal
- Frontiers in Radiology
- Published
- 2024-11-21
- DOI
- https://doi.org/10.3389/fradi.2024.1460889
- Citations
- 9
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 3.13