title: Computer-assisted liver tumor surgery using a novel semiautomatic and a hybrid semiautomatic segmentation algorithm.
abstract: We developed a medical image segmentation and preoperative planning application which implements a semiautomatic and a hybrid semiautomatic liver segmentation algorithm. The aim of this study was to evaluate the feasibility of computer-assisted liver tumor surgery using these algorithms which are based on thresholding by pixel intensity value from initial seed points. A random sample of 12 patients undergoing elective high-risk hepatectomies at our institution was prospectively selected to undergo computer-assisted surgery using our algorithms (June 2013-July 2014). Quantitative and qualitative evaluation was performed. The average computer analysis time (segmentation, resection planning, volumetry, visualization) was 45 min/dataset. The runtime for the semiautomatic algorithm was <0.2 s/slice. Liver volumetric segmentation using the hybrid method was achieved in 12.9 s/dataset (SD ± 6.14). Mean similarity index was 96.2 % (SD ± 1.6). The future liver remnant volume calculated by the application showed a correlation of 0.99 to that calculated using manual boundary tracing. The 3D liver models and the virtual liver resections had an acceptable coincidence with the real intraoperative findings. The patient-specific 3D models produced using our semiautomatic and hybrid semiautomatic segmentation algorithms proved to be accurate for the preoperative planning in liver tumor surgery and effectively enhanced the intraoperative medical image guidance.
authors: Hepatobiliary and Pancreatic Unit, Department of Surgery, University Hospital of Patras, 26500, Patras, Greece. azygomalas@upatras.gr.|Computer Engineering and Informatics Department, School of Engineering, University of Patras, 26500, Rio, Patras, Greece. azygomalas@upatras.gr.
authors: Apollon
authors: A
authors: Zygomalas
authors: Hepatobiliary and Pancreatic Unit, Department of Surgery, University Hospital of Patras, 26500, Patras, Greece.
authors: Dionissios
authors: D
authors: Karavias
authors: Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780, Zografou, Athens, Greece.
authors: Dimitrios
authors: D
authors: Koutsouris
authors: Hepatobiliary and Pancreatic Unit, Department of Surgery, University Hospital of Patras, 26500, Patras, Greece.
authors: Ioannis
authors: I
authors: Maroulis
authors: Hepatobiliary and Pancreatic Unit, Department of Surgery, University Hospital of Patras, 26500, Patras, Greece.
authors: Dimitrios D
authors: DD
authors: Karavias
authors: Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780, Zografou, Athens, Greece.
authors: Konstantinos
authors: K
authors: Giokas
authors: Computer Engineering and Informatics Department, School of Engineering, University of Patras, 26500, Rio, Patras, Greece.
authors: Vasileios
authors: V
authors: Megalooikonomou
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008099:Liver / Q000473:pathology / Q000601:surgery; D008113:Liver Neoplasms / Q000000981:diagnostic imaging / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D009929:Organ Size; D015203:Reproducibility of Results; D025321:Surgery, Computer-Assisted
keywords: Computer-assisted surgery; Hepatectomy; Liver neoplasms; Liver segmentation; Liver tumor