Enterprise Imaging

Enterprise imaging brings together all imaging exams, patient data and reports from across a healthcare system into one location to aid efficiency and economy of scale for data storage. This enables immediate access to images and reports any clinical user of the electronic medical record (EMR) across a healthcare system, regardless of location. Enterprise imaging (EI) systems replace the former system of using a variety of disparate, siloed picture archiving and communication systems (PACS), radiology information systems (RIS), and a variety of separate, dedicated workstations and logins to view or post-process different imaging modalities. Often these siloed systems cannot interoperate and cannot easily be connected. Web-based EI systems are becoming the standard across most healthcare systems to incorporate not only radiology, but also cardiology (CVIS), pathology and dozens of other departments to centralize all patient data into one cloud-based data storage and data management system.

Female Medical Research Scientist Working with Brain Scans

Chan Zuckerberg Initiative to help fund repeat imaging of 60,000 patients

The ambitious project seeks to exponentially increase new data within the U.K. Biobank, a prominent large-scale biomedical database and research resource. 

Self-supervised AI ‘reads’ radiology reports to speed algorithm development

A machine learning system has come along that needs no human labeling of data for training yet matches radiologists at classifying diseases on chest X-rays—including some that the model was not specifically taught to detect.

Intelerad acquires Life Image, becomes 'largest medical image exchange network in the world'

The acquisition represents a significant advance in interoperability and will combine networks that total over 80 billion images globally, including data from institutions such as Mayo Clinic, Cleveland Clinic and New York Presbyterian Hospital.

Thumbnail

Might AI automation improve peer review?

With the software’s help, the ratio of CTs requiring radiologist review to missed findings identified was 10:1, experts shared, adding that without the help of AI that ratio would be at least 66:1. 

M&A mergers and acquisitions business deal

Intelerad’s $500M investment creates image-sharing network managing 80B images

Suggesting the move will significantly advance radiology’s specialtywide imperative to “ditch the disk,” Montreal-based Intelerad Medical Systems has announced it is acquiring a longtime competitor in the image-exchange space.

Thumbnail

Deep learning reconstruction levels playing field between 1.5T and 3T MRI exams

Denoising using deep learning techniques can boost the performance of 1.5T MR brain imaging, resulting in quality comparable or superior to 3T imaging. 

Thumbnail

'Radiologic serendipity' a common trigger event that ends in thyroid surgery in asymptomatic patients

In this cohort, experts found that just 34% of surgeries were performed on symptomatic patients, which shifted their focus to other potential modes of detection.

coronavirus COVID-19 vaccine vaccination

MRI analysis offers new insight into vaccine-related lymphadenopathy in the general population

To date, research pertaining to reactive lymphadenopathy has focused mostly on patients with cancer who are routinely staged and monitored via PET/CT or in women undergoing breast cancer screening and/or imaging with mammography and ultrasound.