Purpose To evaluate the performance of an artificial intelligence (AI) tool using a deep learning algorithm for detecting hemorrhage, mass effect, or hydrocephalus (HMH) at non-contrast material-enhanced head computed tomographic (CT) examinations and to determine algorithm performance for detection of suspected acute infarct (SAI).
Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of “big imaging data,” as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence. These capabilities, along with documentation and guidance, explaining how to interact with a commercial system (e.g., PACS, EHR, commercial database) that currently exists in clinical environments, are to be made freely available.
Come see our presentation on “Building Tools for Artificial Intelligence Research in Medical Imaging” on Wed. October 24th presenting will be Dr. BS Erdal, Dr. Vikash Gupta, and Dr. Mutlu Demirer!
NVIDIA’s GPU Technology Conference (GTC) is the premier AI and deep learning conference series, providing you with training, insights, and direct access to experts from NVIDIA and other leading organizations.
October 22-24, 2018
March 17-21, 2019
Silicon Valley, California