Biomedical subjects

C Chronaki

Publications and source records attributed to C Chronaki.

3 recordsLinked to original sources

PubMed1997

Virtual workspaces in I2Cnet.

The objective of I2Cnet (Image Indexing by Content network) is to provide network-transparent content-based access to medical image archives as an Internet/intranet value-added service. Through a typical web browser, healthcare professionals interact with image collections, browse images similar to a query image, compare these images to images from other collections, and contribute their own images or comments. Specific I2Cnet services available on the World Wide Web (WWW) include image processing and feature extraction, content- and annotation-based search for images and image-related information, and authoring of annotations and image descriptions. Virtual workspaces provide the necessary mechanisms to support user sessions in I2Cnet, providing for service interoperability, persistence, and user interaction. In the course of a user session, which begins with a workspace log-in and ends explicitly with a workspace log-out or implicitly by exiting the browser, virtual workspaces maintain the common context.

Computer Communication Networks↗

PubMed1997

The I2Cnet service architecture paradigm.

The main objective of the Image Indexing by Content network (I2Cnet) is to provide network-transparent content-based access to medical image archives based on a collection of interoperable Internet/intranet added-value services. This paper discusses I2Cnet, focusing on its service architecture paradigm. I2Cnet services such as image annotation, processing, description, and content-based retrieval, as well as the on-line collaboration service are presented. Exemplary user sessions are used to illustrate how virtual workspaces facilitate the interoperation of I2Cnet services, following the "network computer" approach to information management.

Abstracting and Indexing↗

PubMedDate not supplied

I2C: a system for the indexing, storage, and retrieval of medical images by content.

Image indexing, storage, and retrieval based on pictorial content is a feature of image database systems which is becoming of increasing importance in many application domains. Medical image database systems, which support the retrieval of images generated by different modalities based on their pictorial content, will provide added value to future generation picture archiving and communication systems (PACS), and can be used as a diagnostic decision support tools and as a tool for medical research and training. We present the architecture and features of I2C, a system for the indexing, storage, and retrieval of medical images by content. A unique design feature of this architecture is that it also serves as a platform for the implementation and performance evaluation of image description methods and retrieval strategies. I2C is a modular and extensible system, which has been developed based on object-oriented principles. It consists of a set of cooperating modules which facilitate the addition of new graphical tools, image description and matching algorithms. These can be incorporated into the system at the application level. The core concept of I2C is an image class hierarchy. Image classes encapsulate different segmentation and image content description algorithms. Medical images are assigned to image classes based on a set of user-defined attributes such as imaging modality, type of study, anatomical characteristics, etc. This class-based treatment of images in the I2C system achieves increased accuracy and efficiency of content-based retrievals, by limiting the search space and allowing specific algorithms to be fine-tuned for images acquired by different modalities or representing different parts of the anatomy.

Abstracting and Indexing↗