Title :
Image-guided preparation of the calot´s triangle in laparoscopic cholecystectomy
Author :
Akbari, Hamed ; Kosugi, Yukio ; Khorgami, Zhamak
Author_Institution :
Tokyo Inst. of Technol., Yokohama, Japan
Abstract :
Laparoscopic cholecystectomy is the most common way to remove the gallbladder nowadays. Compared to open surgery, laparoscopy results in shorter hospital stays, reduced postoperative pain, and smaller incisions. Proper localization of the cystic artery is of great importance in laparoscopic cholecystectomy in order to ensure safe stapling and avoiding injury to the artery. In this study, we evaluate an image-guided method for artery detection. The performance of this method was evaluated in detecting arteries in 35 laparoscopic cholecystectomy patients. This method uses the artery´s pulse to distinguish it from veins and biliary ducts. By subtracting the systolic and diastolic images, the change regions are detected and shown on a monitor. In 35 laparoscopic cholecystectomy procedures the method can correctly detect all arteries that are not too deep and can move superficial tissues with zero false-negative and 12% false-positive rates. Using the second mode of the method that needs more time for processing, the false-positive rate decreased to 4% with zero false-negative. The image-guided technique is a sensitive, noninvasive, and cost-effective method to detect arteries in laparoscopic cholecystectomy, even if it is covered with fat or other tissues. It is possible to install the program on any ordinary laparoscopy set and it displays the artery´s region on the monitor.
Keywords :
biological organs; biomedical optical imaging; blood vessels; endoscopes; medical image processing; surgery; Calot´s triangle; artery detection; cystic artery; diastolic image; gallbladder; image processing method; image subtraction; image-guided method; image-guided preparation; laparoscopic cholecystectomy; systolic image; Algorithms; Artificial Intelligence; Cholecystectomy, Laparoscopic; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Surgery, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5333766