Mastering the Art of MammographyJul 11th, 2014Fort Worth, TXUShttps://store.aheconline.com/index.php?route=product/product&path=59&product_id=1148This course is designed for both front-line mammographers and interpreting physicians.Latest in HomeUnstable brain networks may drive multiple sclerosis fatigueMarch 9, 2026AI-calculated BAC on mammograms predicts cardiovascular disease in womenMarch 9, 2026ECR: Cardiac imaging is at the 'heart' of precision medicineMarch 6, 2026Ultrasound MinnieCast, Episode 3: Focused ultrasound brings hope to patientsMarch 6, 2026
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
