On May 15th, Andrew Shawa, a research student from the Enterprise Medical Imaging in Zambia (EMIZ) project, presented an engaging colloquium titled "Intelligent DICOM Viewers: Orthanc Plugin for Semi-Automated Interpretation of Medical Images." This talk was part of the 2023/24 CSC 5741 seminar series, aimed at bridging the gap between academic research and practical applications in medical imaging.
Andrew Shawa's presentation centered on the development and implementation of an Orthanc Web-based PACS plugin DICOM Viewer, designed to facilitate semi-automated interpretation of medical images using Artificial Intelligence (AI). Specifically, it highlighted the integration of AI services, focusing on Pneumonia Classification and Detection models implemented in Python.
The presentation underscored the transformative impact that AI-enhanced DICOM Viewers could have on medical imaging practices by enhancing efficiency and accuracy in radiological workflows, ultimately benefiting patient care. It exemplifies the critical role of innovative research in driving advancements in healthcare technology and highlights the promising future of AI integration in medical imaging.
Presentation video:
Presentation slides:
As part of the ongoing 2023/24 CSC 5741 course series, this colloquium not only provided valuable insights but also inspired future research and development in the field of intelligent medical imaging solutions.