Web-based Multi-dimensional Medical Image Collaborative Annotation System

Medical image annotation is playing an increasingly important role in clinical diagnosis and medical research. Existing medical image annotation is faced with many demands and challenges. 1) The emergence and sharp increasing speed of multi-dimensional medical images. 2) Image annotation includes not only text annotation, but also graphical annotation, clinical diagnostic information and image content features information. 3) Uneven distribution of medical resources, which makes difficult to aggregate group intelligence from a much larger scale of distributed experts. Most of the present study is texted based within hospitals on single images annotation. It is difficult to organize and manage unstructured medi-cal image annotation and collaborative sharing information. This paper dedicated to the research on collaborative web-based multi-dimensional medical image an-notation and retrieval in order to address these problems, overcome the shortcom-ing of traditional thin client and facilitate medical experts in different locations to exchange views and comments,. It proposed 1) a system architecture that provides authoring, storing, querying, and exchanging of annotations, and supports web-based collaboration. 2) 2D multi-frame and 3D medical image collaborative anno-tation data model. 3) Collaborative annotation mechanisms

Retrieval of high-dimensional visual data: current state, trends and challenges ahead

Information retrieval algorithms have changed the way we manage and use various data sources, such as images, music or multimedia collections. First, free text information of documents from varying sources became accessible in addition to structured data in databases, initially for exact search and then for more probabilistic models. Novel approaches enable content-based visual search of images using computerized image analysis making visual image content searchable without requiring high quality manual annotations. Other multimedia data followed such as video and music retrieval, sometimes based on techniques such as extracting objects and classifying genre. 3D (surface) objects and solid textures have also been produced in quickly increasing quantities, for example in medical tomographic imaging. For these two types of 3D information sources, systems have become available to characterize the objects or textures and search for similar visual content in large databases. With 3D moving sequences (i.e., 4D), in particular medical imaging, even higher-dimensional data have become available for analysis and retrieval and currently present many multimedia retrieval challenges. This article systematically reviews current techniques in various fields of 3D and 4D visual information retrieval and analyses the currently dominating application areas. The employed techniques are analysed and regrouped to highlight similarities and complementarities among them in order to guide the choice of optimal approaches for new 3D and 4D retrieval problems. Opportunities for future applications conclude the article. 3D or higher-dimensional visual information retrieval is expected to grow quickly in the coming years and in this respect this article can serve as a basis for designing new applications