Explore a comprehensive lecture on understanding scanner utilization through real-time DICOM metadata extraction. Learn about Niffler, an open-source DICOM framework for machine learning pipelines and processing workflows. Discover how this framework analyzes scanner utilization in healthcare networks by retrieving radiology images and processing metadata. Compare the accuracy of this method to traditional RIS data approaches. Gain insights into the implementation of Niffler for real-time and on-demand execution of machine learning pipelines on radiology images. Delve into topics such as data integration, federation, challenges in healthcare data processing, and the architecture of distributed environments for medical imaging analysis.