Medical software developer Blackford Analysis is highlighting the results of a study on the company's image analysis software.
Researchers found that radiologists interpreting images on a PACS workstation integrated with the company's automatic alignment technology needed less time to match lung nodule locations between current and prior chest CT exams.
The study, scheduled for publication later this year, retrospectively identified 27 subjects from Stony Brook Medical Center with nodules in two chest CT exams within three years. The researchers measured the time for board-certified radiologists to match each of the 112 nodules in prior exams to the same location in current exams in PACS using two volume alignment methods:
- Manual rigid alignment, where a radiologist synchronized scrolling manually at the most superior slice where air was visible in the right lung
- Automatic deformable alignment, where Blackford's PACS-integrated software performed automatic deformable alignment of current and prior chest CT exams
Preliminary study results indicate time savings of greater than 55% with automatic deformable alignment compared to manual alignment of current and prior images.




















![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=112&q=70&w=112)