Paul Davis[email protected]HomeResponsive - Request ReprintsAugust 5, 2014HomeResponsive - Three things to look for in your next online adAugust 5, 2014HomeResponsive - Six tips to make your e-mail broadcasts more responsiveAugust 5, 2014HomeResponsive - Don't just give it away...August 5, 2014HomeResponsive - Rich Media: The power of being richAugust 5, 2014HomeResponsive - Defining Your SuccessAugust 5, 2014HomeResponsive - Agents of Change: The new wave of crawlers, spiders and botsAugust 5, 2014HomeResponsive - Lost in Translation...August 5, 2014HomeResponsive - Mismatched GoalsAugust 5, 2014HomeResponsive - Introducing the new Portrait ad formatAugust 5, 2014Page 1 of 3Next PageTop StoriesCardiac ImagingECR: Cardiac imaging is at the 'heart' of precision medicineThe heart beats 2.5 billion times in a person's lifetime and "never has a day off," presenter Michelle Williams, PhD, noted.UltrasoundUltrasound MinnieCast, Episode 3: Focused ultrasound brings hope to patientsWomens ImagingECR: LLMs help patients understand breast imaging reportsCTDL segmentation of chest muscle volume shows promise for COPD patientsCareersHPI: Workforce attrition higher in radiology subspecialties
![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&fit=crop&h=167&q=70&w=250)
![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)
