- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
R2 readies virtual colonoscopy CAD for FDA approval
R2 Technology has unveiled at the RSNA meeting a robust version of computer-aided detection technology programmed to find colon polyps. The company plans to take this latest iteration of CAD, first shown at the 2002 RSNA meeting, to the FDA in next year.
R2 Technology has unveiled at the RSNA meeting a robust version of computer-aided detection technology programmed to find colon polyps. The company plans to take this latest iteration of CAD, first shown at the 2002 RSNA meeting, to the FDA in next year.
"This is going to be one of the hottest CAD areas because it will open up virtual colonoscopy as a modality itself," said R2 CEO Michael Klein.
One reason virtual colonoscopy has not taken off is the difficulty physicians have reading the images, according to Klein. Another reason is that patients still must evacuate the colon before the examination. CAD could help alleviate both problems
CAD for colonoscopy has the potential to speed up the exam and eliminate the need to prep the bowel. R2's virtual colonoscopy system can electronically remove stool from colon scans by distinguishing differences in density between fecal material and polyps.
The system also simplifies interpretation of virtual colonoscopy scans. By taking radiologists directly to areas where suspicious nodules may be present, CAD may trim interpretation time down to a few minutes, Klein said.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
Mammography-Based AI Abnormality Scoring May Improve Prediction of Invasive Upgrade of DCIS
April 9th 2024Emerging research suggests that an artificial intelligence (AI) score of 75 or greater for mammography abnormalities more than doubles the likelihood of invasive upgrade of ductal carcinoma in situ (DCIS) diagnosed with percutaneous biopsy.
Mammography Study: AI Improves Breast Cancer Detection and Reduces Reading Time with DBT
April 3rd 2024An emerging artificial intelligence (AI) model demonstrated more than 12 percent higher specificity and reduced image reading time by nearly six seconds in comparison to unassisted radiologist interpretation of digital breast tomosynthesis (DBT) images.
