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Tomographic US spots ventricular septal defect
Tomographic ultrasound imaging on 4D volumes of fetal chest obtained with spatiotemporal image correlation and color Doppler shows good retrieval of diagnostic cardiac planes in fetuses with ventricular septal defects, according to an Italian study.
Tomographic ultrasound imaging on 4D volumes of fetal chest obtained with spatiotemporal image correlation and color Doppler shows good retrieval of diagnostic cardiac planes in fetuses with ventricular septal defects, according to an Italian study.
Investigators retrospectively evaluated eight fetuses with ventricular septal defects (single in seven and double in one) between 20 and 33 weeks gestation. They found that all of the defects were correctly identified with interslice distance in the tomographic ultrasound imaging function ranging from 0.8 to 2 mm without the need to further manipulate the volume. The researchers say the findings may improve diagnostic accuracy for this condition. The study was reported in July in the Journal of Ultrasound in Medicine.
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.
