Collaborative Image Annotation in Ophthalmology

描述（由申请人提供）：长期目标是开发一个商业的基于互联网的协作图像注释系统，该系统将被临床和临床试验环境中的医生使用。这个软件将实现两个目标。首先，它将显著提高读取、解释和跟踪图像病理区域的客观性、方便性和准确性。其次，它将促进多个临床中心的医生和支持人员之间的有效协作。该软件将体现三项技术创新：丰富的注释与病理区域绑定在图像中；基于web浏览器的图像标记和物理属性的自动计算；协作技术可以安全地检索、存储和搜索丰富的注释。一期和二期将重点研究和开发该技术与眼科图像。

DESCRIPTION (provided by applicant): Longer-term objective is to develop a commercial internet-based collaborative image annotation system that will be used by physicians in both clinical and clinical trials settings. This software will accomplish two goals. First, it will significantly enhance the objectivity, ease and accuracy in reading, interpreting and tracking areas of pathology in an image. Second, it will facilitate effective collaboration among physicians and support personnel at multiple clinical centers. This software will embody three technological innovations: rich annotations tied to areas of pathology in an image; web-browser based markings of images and automated computation of physical properties; and collaborative technology to securely retrieve, store and search rich annotations. Phase I and II will focus on research and development of this technology with ophthalmic images. Research approach is to: Collect functional and technical requirements from two sources the Fundus Photography Reading Center (FPRC) in Madison, WI, and Univ. of Florida Ophthalmology (UFO) in Jacksonville, FL; design and develop the collaborative image annotation system with Ophthalmic images; beta test the application at FPRC and UFO. Benefits will be: superior quality data through objective reading, interpretation and tracking (over multiple visits) of areas of pathology in images; faster turn around on image reading and interpretation through paperless, web-based user-friendly system; and easier searching, statistical analysis and documentation of results. Potential commercial applications are: Ophthalmology reading centers; Collaboration system for clinical trials in image related medical areas; Clinical diagnosis, treatment and monitoring of diseases based on sequential imaging, Computer-based instruction, training and testing on image related medical topics.