SenseCare: A Research Platform for Medical Image Informatics and Interactive 3D Visualization
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Abstract (arXiv)
Clinical research on smart health has an increasing demand for intelligent and clinic-oriented medical image computing algorithms and platforms that support various applications. To this end, we have developed SenseCare research platform, which is designed to facilitate translational research on intelligent diagnosis and treatment planning in various clinical scenarios. To enable clinical research with Artificial Intelligence (AI), 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. In addition, SenseCare is clinic-oriented and supports a wide range of clinical applications such as diagnosis and surgical planning for lung cancer, pelvic tumor, coronary artery disease, etc. SenseCare provides several appealing functions and features such as advanced 3D visualization, concurrent and efficient web-based access, fast data synchronization and high data security, multi-center deployment, support for collaborative research, etc. In this report, we present an overview of SenseCare as an efficient platform providing comprehensive toolkits and high extensibility for intelligent image analysis and clinical research in different application scenarios. We also summarize the research outcome through the collaboration with multiple hospitals.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Apr 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 3; 2025: 3; 2026: 1.
11 papers.
- 2023UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentationcited by 21
- 2021Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformationcited by 15
- 2022PyMIC: A deep learning toolkit for annotation-efficient medical image segmentationcited by 14
- 2021SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matchingcited by 12
- 2025MetaSSL: A General Heterogeneous Loss for Semi-Supervised Medical Image Segmentationcited by 6
- 2024OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicinecited by 5
- 2024VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Annotation-Free Pathological Image Classificationcited by 5
- 2024REHRSeg: Unleashing the Power of Self-Supervised Super-Resolution for Resource-Efficient 3D MRI Segmentationcited by 2
- 2025VBCD: A Voxel-Based Framework for Personalized Dental Crown Designcited by 2
- 2026MADCrowner: Margin Aware Dental Crown Design with Template Deformation and Refinementcited by 1
- 2025Dissecting the Dental Lung Cancer Axis via Mendelian Randomization and Mediation Analysiscited by 0
- 2026MADCrowner: Margin Aware Dental Crown Design with Template Deformation and Refinement5 Mar 2026
- 2025MetaSSL: A General Heterogeneous Loss for Semi-Supervised Medical Image Segmentation1 Sep 2025
- 2025Dissecting the Dental Lung Cancer Axis via Mendelian Randomization and Mediation Analysis24 Jul 2025
- 2025VBCD: A Voxel-Based Framework for Personalized Dental Crown Design23 Jul 2025
- 2024REHRSeg: Unleashing the Power of Self-Supervised Super-Resolution for Resource-Efficient 3D MRI Segmentation14 Oct 2024
- 2024VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Annotation-Free Pathological Image Classification23 Mar 2024
- 2024OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicine28 Feb 2024
- 2023UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation19 Sep 2023
- 2022PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation19 Aug 2022
- 2021Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation8 Jul 2021
- 2021SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching12 Apr 2021