Dr. David Clunie[email protected]PACS/VNAImaging experts mull over color challengesColor images are technically difficult to deal with, creating a thorny issue that's growing as PACS broadens from radiology and cardiology to include other specialties that use color-heavy images. Medical informatics expert Dr. David Clunie discusses a recent meeting designed to provide a framework for handling color.May 27, 2013BreastBreast tomosynthesis challenges digital imaging infrastructureWhile the advent of digital breast tomosynthesis (DBT) in the U.S. has added an exciting weapon to the breast imaging armamentarium, these new capabilities have also led to significant image management challenges. DBT adopters need to be aware of and plan for issues such as large file sizes and proprietary file formats.March 20, 2013Page 1 of 1Top StoriesMRIUnstable brain networks may drive multiple sclerosis fatigueFatigue affects between 36.5% and 78% of people with multiple sclerosis and can dramatically impair their daily lives.Womens ImagingAI-calculated BAC on mammograms predicts cardiovascular disease in womenCardiac ImagingECR: Cardiac imaging is at the 'heart' of precision medicineUltrasoundUltrasound MinnieCast, Episode 3: Focused ultrasound brings hope to patientsWomens ImagingECR: LLMs help patients understand breast imaging reports
![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)
