Adelaide – EN - Adelaide

Cognitive Radiology for Big Data Projects and In Silico Trials

Objectives

The main objectives to be developed and achieved during aDELAIDE project are:

Algorithms based on Artificial Intelligence capable to detect and automatically classify the quality of the studies depending on the radiological images of the patient.

Implement Artificial Intelligence technologies on the day-to-day of the clinical activity.

Algorithms able to extract the crucial information from medical reports.

A solution that facilitates the identification of patient cohorts for inclusion in clinical trials or retrospective studies, by combining automatic complex analyses of images and radiological reports.

What is aDELAIDE project about?

aDELAIDE stands for DEtection and Localization of AnatomicaL structures for enhanced IDEntification and search of imaging studies. It aims at defining, developing and deploying a solution that allows querying the Picture Archiving and Communication Systems (PACS) based on tags generated from complex image analysis and semantic radiological report mining to facilitate patient cohort generation for clinical trials or research studies.

Radiology departments have huge image databases collected over decades and stored in hospitals’ PACS. However, there is a tremendous opportunity for improvement in making all this image data mineable, since it is not archived, sorted and organized efficiently. Extracting, harvesting and building large-scale annotated image datasets from these databases is greatly important for patient management and clinical development.