Massive Imaging Database Created to Aid Research
By MedImaging International staff writers Posted on 30 May 2017 |
Image: Functional Magnetic Resonance Imaging (fMRI) brain scans intended to identify biomarkers for autism (Photo courtesy of SpectrumNews).
A large healthcare system in the U.S. has announced the creation of a massive, anonymous imaging database that will integrate clinical imaging and electronic health records using data from more than 1 million patients.
The goal of the project is to dramatically improve clinical care and translational research, and enable clinicians to investigate patterns and traits of specific diseases or conditions. The project will help clinicians find common features among large groups of patients, and identify genetic or other similarities that could lead to new diagnostic techniques and treatments. The Imaging Research Warehouse (IRW) was developed by the Mount Sinai Translational and Molecular Imaging Institute (TMII) of the Mount Sinai Health System.
The IRW is intended to advance research in mammography, prostate cancer, genomics, spine injuries, neuro-degenerative diseases, and bowel disease, and has the potential to change the way radiologists read and collect data. Together with the help of machine learning algorithms, radiologists could use the system to better evaluate known abnormalities in imaging scans. Other possible outcomes include new and more accurate Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) imaging protocols and techniques.
Vice Chair, Radiology, Mount Sinai Health System, David Mendelson, MD, professor at the Icahn School of Medicine at Mount Sinai, said, “The Imaging Research Warehouse is a unique resource that will provide large volumes of de-identified images to the research community. This model fills a gap in the new world of healthcare ‘big data.’ The data contained within patients’ radiological images is hard to make use of, and this warehouse is the solution to expose this information for analysis.”
The goal of the project is to dramatically improve clinical care and translational research, and enable clinicians to investigate patterns and traits of specific diseases or conditions. The project will help clinicians find common features among large groups of patients, and identify genetic or other similarities that could lead to new diagnostic techniques and treatments. The Imaging Research Warehouse (IRW) was developed by the Mount Sinai Translational and Molecular Imaging Institute (TMII) of the Mount Sinai Health System.
The IRW is intended to advance research in mammography, prostate cancer, genomics, spine injuries, neuro-degenerative diseases, and bowel disease, and has the potential to change the way radiologists read and collect data. Together with the help of machine learning algorithms, radiologists could use the system to better evaluate known abnormalities in imaging scans. Other possible outcomes include new and more accurate Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) imaging protocols and techniques.
Vice Chair, Radiology, Mount Sinai Health System, David Mendelson, MD, professor at the Icahn School of Medicine at Mount Sinai, said, “The Imaging Research Warehouse is a unique resource that will provide large volumes of de-identified images to the research community. This model fills a gap in the new world of healthcare ‘big data.’ The data contained within patients’ radiological images is hard to make use of, and this warehouse is the solution to expose this information for analysis.”
Latest Radiography News
- Novel Breast Imaging System Proves As Effective As Mammography
- AI Assistance Improves Breast-Cancer Screening by Reducing False Positives
- AI Could Boost Clinical Adoption of Chest DDR
- 3D Mammography Almost Halves Breast Cancer Incidence between Two Screening Tests
- AI Model Predicts 5-Year Breast Cancer Risk from Mammograms
- Deep Learning Framework Detects Fractures in X-Ray Images With 99% Accuracy
- Direct AI-Based Medical X-Ray Imaging System a Paradigm-Shift from Conventional DR and CT
- Chest X-Ray AI Solution Automatically Identifies, Categorizes and Highlights Suspicious Areas
- AI Diagnoses Wrist Fractures As Well As Radiologists
- Annual Mammography Beginning At 40 Cuts Breast Cancer Mortality By 42%
- 3D Human GPS Powered By Light Paves Way for Radiation-Free Minimally-Invasive Surgery
- Novel AI Technology to Revolutionize Cancer Detection in Dense Breasts
- AI Solution Provides Radiologists with 'Second Pair' Of Eyes to Detect Breast Cancers
- AI Helps General Radiologists Achieve Specialist-Level Performance in Interpreting Mammograms
- Novel Imaging Technique Could Transform Breast Cancer Detection
- Computer Program Combines AI and Heat-Imaging Technology for Early Breast Cancer Detection