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.
翻译:智能健康临床研究越来越需要智能和诊所导向型医疗图像计算算法和平台,以支持各种应用。为此目的,我们开发了SenseCare研究平台,旨在便利对各种临床情景的智能诊断和治疗规划进行翻译研究。为了能够与人工智能智能(AI)、SenseCare进行临床研究,SenseCare为不同的任务提供一系列AI工具包,包括图像分割、登记、损伤和从放射学到病理学等各种图像模式的里程碑检测。此外,SenseCare面向诊所,支持一系列广泛的临床应用,例如肺癌、骨盆癌、冠状动脉病等诊断和外科手术规划。SenseCare提供了若干具有吸引力的功能和特征,如高级三维视觉化、同步和高效的网络访问、快速数据同步和高数据安全性、多中心部署、支持合作研究等。我们在本报告中概述了SenseCare,作为一个有效的平台,为不同应用情景的智能图像分析和临床研究提供综合工具包和高外延率。我们还通过多种合作总结研究成果。