Congratulations to NCITA researchers Dr Lorena Escudero Sanchez (University of Cambridge), Dr Mohammad Al Sa’d (Imperial College London), Dr Simon Doran (ICR) and colleagues on their recent publication Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case in Diagnostics open access journal on 22 August 2023.

The team have developed a prototype pipeline, which combines custom AI-based workflows and visual application tools based entirely on open-source software, for integration of radiology tasks such as segmentation and prediction into the clinical research setting. 

The group have reported the establishment of deep learning models for ovarian tumour segmentation from CT images with the integrated OHIF viewer plugin to XNAT, developed by NCITA repository unit members (Tomography, 2022) as an example workflow, to illustrate the potential of the prototype pipeline to bridge the gap between AI developments and their usage by clinicians.