An Improved Algorithm for Coronary Bypass Anastomosis Segmentation in Epicardial Ultrasound Sequences.
Epicardial ultrasound (EUS) can be used for intra-operative quality assessment of coronary artery bypass anastomoses. To quantify the anastomotic quality from EUS images, the area of anastomotic structures has to be extracted from EUS sequences. Currently, this is done manually as no objective methods are available. We used an automatic anastomosis segmentation algorithm to extract the area of anastomotic structures from in vivo EUS sequences obtained from 16 porcine anastomoses. The algorithm consists of four major components: vessel detection, vessel segmentation, segmentation quality control and inter-frame contour alignment. The segmentation accuracy was assessed using m-fold cross-validation based on 830 manual segmentations of the anastomotic structures. A Dice coefficient of 0.879 (±0.073) and an absolute area difference of 16.95% (±17.94) were obtained. The proposed segmentation algorithm has potential to automatically extract the area of anastomotic structures.
Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. Electronic address: asj@hst.aau.dk.
Alex Skovsbo
AS
Jørgensen
Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
Samuel Emil
SE
Schmidt
Department of Cardiothoracic Surgery, Center for Cardiovascular Research, Aalborg University Hospital, Aalborg, Denmark; Institute of Clinical Research, Skejby Sygehus, Aarhus University Hospital, Aarhus, Denmark.
Niels-Henrik
NH
Staalsen
Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
Lasse Riis
LR
Østergaard
D000465:Algorithms; D000714:Anastomosis, Surgical; D000818:Animals; D001026:Coronary Artery Bypass; D003331:Coronary Vessels / Q000000981:diagnostic imaging* / Q000601:surgery*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D023421:Models, Animal; D013552:Swine; D014463:Ultrasonography / Q000379:methods*
Coronary artery bypass surgery; Epicardial ultrasound; Quality assessment; Segmentation; Vessels