Segmentation of vessel tree from cine-angiography images for intraoperative clinical evaluation

The assessment of vascular complexity in the lower limbs provides relevant information about peripheral artery diseases, with a relevant impact on both therapeutic decisions and on prognostic estimation. Such evaluation is currently carried out by human operators via visual inspection of cine-angiograms, resulting in conflicting results and scorings that are largely operator-dependent, mostly because of the technical difficulties in the quantification of vascular network and its flow capability. We propose a new method to automatically segment the vessel tree from cine-angiography video for intraoperative clinical evaluation, in order to improve the clinical interpretation of the complexity of vascular collaterals in Peripheral Arterial Occlusive Disease (PAOD) patients.