Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking

ArXi:2605.23118v1 Announce Type: cross Tracking tumor lesions across serial CT scans is essential for oncological response assessment. Existing automated methods face a fundamental trade-off: end-to-end trackers achieve high automation but offer no opportunity to correct silent tracking failures, while decoupled registration-segmentation pipelines permit user verification yet discard the lesion's prior appearance, limiting accuracy in ambiguous cases.