Paper Info
Title
Laparoscopic Image-Guided System Based on Multispectral Imaging for the Ureter Detection.
Abstract
The iatrogenic ureter injury is a common medical negligence in the gynecology, abdominal, and urinary surgeries. Anatomically, the ureter is covered by peritoneum and connective tissue, and the doctor cannot observe it directly in surgery. The ureter injury may cause significant complications for patients and medical disputes. It is important to indicate the ureter position for aided surgery of the doctor. To provide ureter position for doctors in the laparoscopic surgery, we design an image-guided endoscope system that includes a novel endoscopic video system with a visible-light camera and an infrared camera. The visible-light camera is to capture the coeliac image and the infrared camera is to capture the ureter position, simultaneously. To extract accurate ureter position in the infrared image, we also propose a self-adaptive threshold segmentation algorithm to extract the real ureter position as accurately as possible. The self-adaptive threshold and scattering factor are taken in to full account for the ureter segmentation. In addition, the scattering property of light is also discussed to choose the optimal light. Finally, we design and develop the image-guided endoscope system, and experiment it on the animal. The experimental results demonstrate that the proposed image-guided endoscope system achieves 93.8% and 90.6% in terms of true positive rate and positive predictive value, respectively. The processing speed of the proposed algorithm can reach about 165 frames per second (f/s), and the frame rate is far faster than the frame rate (30 f/s) of the traditional endoscope system. The accuracy and processing ability of the system can satisfy the clinical demand. The iatrogenic ureter injury may be decreased when the surgeons perform the operations with the ureter position displayed in real time.
Year
DOI
Venue
2019
10.1109/ACCESS.2018.2889138
IEEE ACCESS
Keywords
Field
DocType
Endoscope system,ureter injury,image-guided,multispectral imaging,ureter detection
Endoscope,Ureter,Computer vision,Laparoscopic surgery,Infrared image,Computer science,Segmentation,Multispectral image,Computer network,Frame rate,Artificial intelligence,True positive rate
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Feng Yu101.01
Enmin Song217624.53
Hong Liu39618.53
Jun Zhu42613.25
Chih-Cheng Hung54613.39