- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
Image wavelet watermarking addresses HIPAA loophole
A multicast "fingerprinting" solution based on image adaptive wavelet watermarking could prevent authorized recipients from releasing images to unauthorized parties.
A multicast "fingerprinting" solution based on image adaptive wavelet watermarking could prevent authorized recipients from releasing images to unauthorized parties.
Current digital image security and privacy protection schemes necessitated by the Health Insurance Portability and Accountability Act provide no mechanism for sending images to unauthorized parties. Researchers at the University of Washington address the issue (Comput Med Imaging Graph 2005;29(5):367-383).
A broadcast image would need to be decoded by watermark keyholders before the image could be used for diagnostic purposes. Assuming a unique watermark per user, watermarking can be used as fingerprinting.
During the process of decoding, two fingerprints that correspond to the original sender and the recipient who performs the decoding are imprinted onto the image.
Researchers considered system implementation issues and completed an analytical performance evaluation. Simulation results conducted on 31 images from five modalities confirmed that the fingerprinted images were of higher quality when compared with 10:1 JPEG compressed images. They withstood various image processing steps, including low-pass filter, high-pass filter, JPEG compression, cropping, and averaging attack, according to the researchers.
Study Reaffirms Low Risk for csPCa with Biopsy Omission After Negative Prostate MRI
December 19th 2024In a new study involving nearly 600 biopsy-naïve men, researchers found that only 4 percent of those with negative prostate MRI had clinically significant prostate cancer after three years of active monitoring.
Study Examines Impact of Deep Learning on Fast MRI Protocols for Knee Pain
December 17th 2024Ten-minute and five-minute knee MRI exams with compressed sequences facilitated by deep learning offered nearly equivalent sensitivity and specificity as an 18-minute conventional MRI knee exam, according to research presented recently at the RSNA conference.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.
