Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction.

Purpose: Personalized interpretation of medical images is critical for optimum patient care, but current tools available to physicians to perform quantitative analysis of patient's medical images in real time are significantly limited. In this work, we describe a novel platform within PACS for volumetric analysis of images and thus development of large expert annotated datasets in parallel with radiologist performing the reading that are critically needed for development of clinically meaningful AI algorithms. Specifically, we implemented a deep learning-based algorithm for automated brain tumor segmentation and radiomics extraction, and embedded it into PACS to accelerate a supervised, end-to- end workflow for image annotation and radiomic feature extraction.

Exophytic External Occipital Protuberance Prevalence Pre- and Post-iPhone Introduction: A Retrospective Cohort.

: In controversial fashion, the presence of an enlarged external occipital protuberance has been recently linked to excessive use of handheld electronic devices. We sought to determine the prevalence of this protuberance in a diverse age group of adults from two separate time periods, before and approximately 10 years after the release of the iPhone, to further characterize this theory, as if indeed valid, such a relationship could direct preventative behavior. : Eighty-two cervical spine radiographs between March 7, 2007 through June 29, 2007 and 147 cervical spine radiographs between October 25, 2017 through January 1, 2018 were reviewed for the presence or absence of an exophytic external occipital protuberance.