- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
Automated process spots subtle tumor changes
Researchers at the Mayo Clinic in Rochester, MN, and the University of Southern California have developed automated techniques to better document changes to brain tumors occurring over time.
Researchers at the Mayo Clinic in Rochester, MN, and the University of Southern California have developed automated techniques to better document changes to brain tumors occurring over time.
The researchers at the Mayo Clinic described the most common approaches to change detection, ranging from manual inspection, measurement sampling, and volumetrics to warping and temporal analysis (J Digital Imaging, e-pub 29 June 2004).
The paper suggests a number of technical approaches for separating acquisition-related changes from pathology-related changes, including preacquisition registration of scans, scaling correction, subvoxel registration, and change computation.
MRI-Based AI Radiomics Model Offers 'Robust' Prediction of Perineural Invasion in Prostate Cancer
July 26th 2024A model that combines MRI-based deep learning radiomics and clinical factors demonstrated an 84.8 percent ROC AUC and a 92.6 percent precision-recall AUC for predicting perineural invasion in prostate cancer cases.
Breast MRI Study Examines Common Factors with False Negatives and False Positives
July 24th 2024The absence of ipsilateral breast hypervascularity is three times more likely to be associated with false-negative findings on breast MRI and non-mass enhancement lesions have a 4.5-fold likelihood of being linked to false-positive results, according to new research.
Can Polyenergetic Reconstruction Help Resolve Streak Artifacts in Photon Counting CT?
July 22nd 2024New research looking at photon-counting computed tomography (PCCT) demonstrated significantly reduced variation and tracheal air density attenuation with polyenergetic reconstruction in contrast to monoenergetic reconstruction on chest CT.
