@Radiology_AI

To determine if the mean curvature of isophotes (MCI), a standard computer vision technique, can be used to improve detection of chronic obstructive pulmonary disease (COPD) at chest CT. In this retrospective study, chest CT scans were obtained in 243 patients with COPD and 31 controls (among all 274: 151 women [mean age, 70 years; range, 44–90 years] and 123 men [mean age, 71 years; range, 29–90 years]) from two community practices between 2006 and 2019. A convolutional neural network (CNN) architecture was trained on either CT images or CT images transformed through the MCI algorithm. Separately, a linear classification based on a single feature derived from the MCI computation (called hMCI1) was also evaluated. All three models were evaluated with cross-validation, using precision-macro and recall-macro metrics, that is, the mean of per-class precision and recall values, respectively (the latter being equivalent to balanced accuracy).