The Use of RIA-Enabled Image Processing Techniques for Constructing Micro-to-Macro Personal Biomedical Atlas

  • Chen, Chi-Hsien, (PI)

Project: A - Government Institutionb - Ministry of Science and Technology

Project Details

Description

This project plans to utilize Rich Internet Applications (RIA) for presenting and processing medical images. This project will adopt Microsoft SliverLight RIA solution for handling 2D, 3D, and microscope medical images. Microsoft Silverlight uses XML-based tags to define graphics drawn in a browser. Geometric shapes, animations, user interfaces, and trigger events can be defined by the XML. Basing on the solution, micro-to-macro clinical images could be presented appropriately on browser. This constitutes an atlas for presenting personal clinical images. Combining with RIA solution, this project also plans to investigate a new approach for dynamic using image processing tools to handle medical images. An eXtensible Imaging Platform (XIP) with open source imaging processing libraries would be integrated in the infrastructure for micro-to-macro images generated in clinical processes. Two different types of image processing would be investigated basing the infrastructure: auto-calculating of bio marker in fluorescence microscope images and auto contouring for radio therapy target volume and dos distribution. Finally, the image processing results and clinical findings would be encoded as standard DICOM Structured Report(SR). Basing on the standard DICOM SR findings, Content-Based Image Retrieval (CBIR) would be constructed in the personal atlas platform. The personal clinical atlas would be integrated with standard clinical document sharing and management infrastructure would be constructed in our other sub-projects. Basing the integration, a personal healthcare platform with rich full clinical information and functionalities would be generated for treatment evaluation and for healthcare management.
StatusFinished
Effective start/end date8/1/107/31/11

Keywords

  • RIA
  • Medical Image Processing
  • DICOM
  • Tumor