Deep Learning in Radiology.

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist.

Building for tomorrow today: opportunities and directions in radiology resident research.

Rationale And Objectives: With rapid scientific and technological advancements in radiological research, there is renewed emphasis on promoting early research training to develop researchers who are capable of tackling the hypothesis-driven research that is typically funded in contemporary academic research enterprises. This review article aims to introduce radiology residents to the abundant radiology research opportunities available to them and to encourage early research engagement among trainees.

Materials And Methods: To encourage early resident participation in radiology research, we review the various research opportunities available to trainees spanning basic, clinical, and translational science opportunities to ongoing research in information technology, informatics, and quality improvement research.

Online social networking for radiology.

Online social networking services have changed the way we interact as a society and offer many opportunities to improve the way we practice radiology and medicine in general. This article begins with an introduction to social networking. Next, the latest advances in online social networking are reviewed, and areas where radiologists and clinicians may benefit from these new tools are discussed.

Radiology research and medical students.

Fostering radiology research among medical students can enhance a student's interest and understanding of radiology and research. It increases the academic productivity of the mentor and the department. Radiology faculty and departments should actively seek to recruit and engage students in research.

Mobile computing for radiology.

The rapid advances in mobile computing technology have the potential to change the way radiology and medicine as a whole are practiced. Several mobile computing advances have not yet found application to the practice of radiology, while others have already been applied to radiology but are not in widespread clinical use. This review addresses several areas where radiology and medicine in general may benefit from adoption of the latest mobile computing technologies and speculates on potential future applications.

Impact of concurrent diagnostic level CT with PET/CT on the utilization of stand-alone CT and MRI in the management of head and neck cancer patients.

Purpose Of The Report: This study aims to determine if the expansion of a PET/CT service to include simultaneous contrast-enhanced CT with PET (PET/DCT) leads to a reduction of supplemental diagnostic CT (sCT) performed within a 6-month period centered around PET/CT for initial treatment planning of patients with head and neck cancers.

Patients And Methods: There were 91 patients with head and neck cancers who had a non-contrast-enhanced PET/CT with CT (PET/aCT), and 153 patients had a PET/DCT. We compared the utilization of sCT before and after PET/aCT or PET/DCT.