General Objective: Design, implement and validate a support system for radiological interpretation and diagnosis under the modality of tele-radiology on a GRID architecture.
The greatest contribution to the system would be to present a tool that allows the recovery of medical images based on both their visual and semantic content using CBIR techniques in medical images. Initially, it would be used for the medical education part in the different advanced levels of education (third and fourth level).
Specific objectives:
- Design the system architecture, taking into account that it will be managed under the GRID architecture. It must be a modular architecture, which will allow the growth and maintenance of the application.
- Define the visual characteristics that will be evaluated in the images for content retrieval (texture, density, shapes) using CBIR techniques in medical imaging.
- Implement a PACS that supports the GRID architecture.
- Design the interface of the system in general, which will allow the use of the application based on profile systems using electronic security techniques.
- Strengthen the training of human talent in the areas of anatomy, radiology, telemedicine, telediagnosis, telehealth, medical specialties, etc.
- Form the bases to carry out different research projects having the availability to handle large volumes of medical images efficiently.
- Offer the infrastructure and space to have images of study cases and to serve as support for students in the health sector, whether in the area of undergraduate, postgraduate medicine, medical technology or the area of biomedicine.
- Develop the technology to offer the remote tele-radiology service and additionally have the inputs to carry out research, carry out intelligent searches for pathologies by similarity, by content, etc.
- Define tools that make it possible to make semantic annotations on the images in order to improve the recovery of the images in the database or improve the visualization of the tissues or areas of interest in the different studies.
- Use GRID technology, in order to take advantage of resources to store large volumes of data and perform high-performance processing, remotely and in real time.
Participating Institutions:
UCUENCA, UTPL, UPS
Participants:
- PhD. Alexandra Cruz.
- PhD. Lizandro Solano.
- PhD. Vinicio Carrera.
- MSc. Patricia Gonzalez.
- Esp. Yoredi Sarmiento.
- MSc. Washington Ramirez
Awarded budget: $49560
Project status: Process – Agreement signing.
