Click on the presentation image below you would like to view.
Hint: start with "Introduction to radiology preprocessing" if new to clinical trials.
Welcome to our publicly available multi-center radiology preprocessing (RP) course that is starting to come together with nearly completed presentation slides in most topic areas. A main objective of this course is to teach RPs basic principles of radiology modalities how they provide required quantification in clinical trials including target lesion selection and consistent measurement.
Radiology preprocessors are sometimes referred to as "post-processors" that measure lesions after or separate from radiologists required for clinical trials, or "scribes" commonly assisting radiologists in private practice or centers without residents in measuring lesions, identifying incidental findings while acting as worklist triage. We have shown that RP augmented radiologist workflow can result in improved target lesion concordance with oncologists on patients in clinical trials, faster radiologist recognition of clinical findings, resulting in earlier referring clinician notification (see reference link below).
We welcome feedback from core labs to optimize the educational value of the course. By request, we will be adding more information and chest CT to include infectious diseases based on need for consistency in labeling pathology for machine learning training. To help promote advances in Artificial Intelligence in radiology, this course additionally helps bridge the gap between coders, engineers and radiologists.
Academic Radiology. 2020 Jan;27(1):96-105
Click the graphic on the left to open our Academic Radiology publication discussing RP augmented radiologist AI - like workflow.
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