Landmark-based feature tracking for endoscopic motion analysis
Automated image analysis and interpretation within computer assisted minimally invasive surgery (MIS) most often depend and rely on manually defined landmarks, visible in endoscopic views. More specific, within many types of applications, such landmarks must be tracked automatically during the intervention. Typical feature tracking approaches are able to track slightly changing landmarks over time, as they occur in endoscopic image sequences, but are originally most often designed to track automatically detected salient points. In this contribution an approach is presented, where the advantages of feature descriptors and corresponding matchers can be used to track manually defined landmarks. Based on such initiated landmark points, local feature detection and tracking utilizing SURF or KLT features as descriptors, is executed. Within the region of interest as a constraint, movements of the detected features can be used to approximate the original landmark movements.