Synthesis of fracture radiographs with deep neural networks.

Purpose: We describe a machine learning system for converting diagrams of fractures into realistic X-ray images. We further present a method for iterative, human-guided refinement of the generated images and show that the resulting synthetic images can be used during training to increase the accuracy of deep classifiers on clinically meaningful subsets of fracture X-rays.

Methods: A neural network was trained to reconstruct images from programmatically created line drawings of those images.

Tanzania IR Initiative: Training the First Generation of Interventional Radiologists.

Despite a population of nearly 60 million, there is currently not a single interventional radiologist in Tanzania. Based on an Interventional Radiology (IR) Readiness Assessment, the key obstacles to establishing IR in Tanzania are the lack of training opportunities and limited availability of disposable equipment. An IR training program was designed and initiated, which relies on US-based volunteer teams of IR physicians, nurses, and technologists to locally train radiology residents, nurses, and technologists.

Predictive value of hyperthermia and intracranial hypertension on neurological outcomes in patients with severe traumatic brain injury.

Background: Intracranial hypertension (ICH) and hyperthermia are common after traumatic brain injury (TBI) and associated with worse neurological outcomes. This study sets out to determine the combined power of temperature and intracranial pressure (ICP) for predicting neurologic outcomes and prolonged length of stay (LOS) following severe TBI.

Methods: High resolution (every 6 seconds) temperature and ICP data were collected in adults with severe TBI from 2008-2010.