Fig. 1.

Illustrated algorithm workflow: (0) Binary lesion masks of four time points; (1) Automatic assignment of labels in longitudinal lesion masks; (2) Identification of lesion label intersections in consecutive lesion masks: Overlaid baseline mask and appropriate follow-up mask; (3) Determining new lesions in the time series: a) Note that the third labelled lesion in follow-up 1 and first and second labels in follow-up 2 do not intersect with lesions of the previous time point; b) new lesions continue in step 2 and were tested for intersection; (4) Assigning a global label to corresponding lesions in a time series: Corresponding local labels and newly identified lesions of the time series were tracked in rows of the LLTM. Note that a consecutive global label was assigned for a new lesion; (5) Determining confluent and separating lesions in the corrected LLTM. Two entries were found for global label 2, which indicates a separated lesion, and two intersections were found for local label 1 in follow-up 3 with previous time points, which indicates a confluent lesion; (6) Relabelled lesion masks: Local labels of the time series of corresponding lesions were overwritten by an appropriate global label.