- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
New search engine optimized for electronic teaching files debuts
A prototype search engine uses advanced content-specific algorithms to efficiently search databases of image files contained in public Medical Imaging Resource Center storage servers. The search engine was developed as a joint project between the Baltimore VA Medical Center and the University of Maryland. The prototype is the alpha version of a vertical search engine designed to match users with radiology-specific content.
A prototype search engine uses advanced content-specific algorithms to efficiently search databases of image files contained in public Medical Imaging Resource Center storage servers. The search engine was developed as a joint project between the Baltimore VA Medical Center and the University of Maryland. The prototype is the alpha version of a vertical search engine designed to match users with radiology-specific content.
Popular search engines cannot provide comprehensive compilations of teaching files in MIRC sites or other radiology information sites that contain case examples. Teaching files are "hidden" from a typical search engine because they are located behind pages of fill-in-the-blank forms.
GoogleMIRC has the ability to obtain and index online storage teaching files located behind these forms. This Web crawler also protects itself from dynamic content, advertisements, and unwanted downloads. Its crawler speed is 1.5 pages per second.
GoogleMIRC provides a portal for searching for specific pages, using a complex algorithm to determine whether each case is relevant. The search engine currently uses 13 servers. In demonstrations at the Lakeside Learning Center, it outperformed commercial search engines by a significant margin.
AI Facilitates Nearly 83 Percent Improvement in Turnaround Time for Fracture X-Rays
December 19th 2023In addition to offering a 98.5 percent sensitivity rate in diagnosing fractures on X-ray, an emerging artificial intelligence (AI) software reportedly helped reduce mean turnaround time on X-ray fracture diagnosis from 48 hours to 8.3 hours, according to new research presented at the Radiological Society of North America (RSNA) conference.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Can an Emerging PET Radiotracer Enhance Detection of Prostate Cancer Recurrence?
December 14th 2023The use of 68Ga-RM2 PET/MRI demonstrated a 35 percent higher sensitivity rate than MRI alone for the diagnosis of biochemical recurrence of prostate cancer, according to research recently presented at the Radiological Society of North America (RSNA) conference.
RSNA 2020: Addressing Healthcare Disparities and Access to Care
December 4th 2020Rich Heller, M.D., with Radiology Partners, and Lucy Spalluto, M.D., with Vanderbilt University School of Medicine, discuss the highlights of their RSNA 2020 session on health disparities, focusing on the underlying factors and challenges radiologists face to providing greater access to care.
Can AI Improve Detection of Extraprostatic Extension on MRI?
December 4th 2023Utilizing a deep learning-based AI algorithm to differentiate between diagnostic and non-diagnostic quality of prostate MRI facilitated a 10 percent higher specificity rate for diagnosing extraprostatic extension on multiparametric MRI, according to research presented at the recent RSNA conference.
Study: Regular Mammography Screening Reduces Breast Cancer Mortality Risk by More than 70 Percent
November 30th 2023Consistent adherence to the five most recent mammography screenings prior to a breast cancer diagnosis reduced breast cancer death risk by 72 percent in comparison to women who did not have the mammography screening, according to new research findings presented at the annual Radiological Society of North America (RSNA) conference.
