- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
The Reading Room: NYU Langone and Facebook AI Partner for Faster MRIs
In this episode, Dr. Michael Recht, chair of the radiology department at New York University Langone Health, discusses the partnership between NYU and Facebook AI that has created an accelerated MRI that is four times as fast as a standard MRI.
Through a partnership with Facebook AI, researchers at NYU Langone Health have trained a neural network that can create MRI images in a fraction of the time needed for standard scans.
In a study published in the American Journal of Roentgenology, the team revealed the radiologists reading the resulting images detected the same abnormalities with the accelerated scans as they did with traditional images.
For more coverage based on industry expert insights and research, subscribe to the Diagnostic Imaging e-Newsletter here.
To reach this determination, they examined two sets of knee MRI scans from 108 patients and created two sets of images -- one using the standard approach and one using the accelerated MRI artificial intelligence model. Based on their analysis, they determined that their 3T fastMRI protocol used four times less data and could produce an image quicker, requiring the patient to spend less time in the scanner.
The goal, Recht said, is to one day apply accelerated MRI to other organs, including the brain.
Can Deep Learning Radiomics with bpMRI Bolster Accuracy for Prostate Cancer Prognosis?
January 22nd 2025An emerging deep learning radiomics model based on biparametric MRI (bpMRI) offered a 14 to 17 percent higher AUC range than PI-RADS scoring for predicting the aggressiveness of prostate cancer, according to new research findings.
Seven Takeaways from New CT and MRI Guidelines for Ovarian Cancer Staging
January 20th 2025In an update of previous guidelines from the European Society of Urogenital Radiology published in 2010, a 21-expert panel offered consensus recommendations on the utility of CT, MRI and PET-CT in the staging and follow-up imaging for patients with ovarian cancer.
Can Generative AI Facilitate Simulated Contrast Enhancement for Prostate MRI?
January 14th 2025Deep learning synthesis of contrast-enhanced MRI from non-contrast prostate MRI sequences provided an average multiscale structural similarity index of 70 percent with actual contrast-enhanced prostate MRI in external validation testing from newly published research.
Can MRI-Based AI Enhance Risk Stratification in Prostate Cancer?
January 13th 2025Employing baseline MRI and clinical data, an emerging deep learning model was 32 percent more likely to predict the progression of low-risk prostate cancer (PCa) to clinically significant prostate cancer (csPCa), according to new research.
