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Augmented reality navigation for liver resection with a stereoscopic laparoscope
- Source :
- Computer methods and programs in biomedicine. 187
- Publication Year :
- 2019
-
Abstract
- Objective Understanding the three-dimensional (3D) spatial position and orientation of vessels and tumor(s) is vital in laparoscopic liver resection procedures. Augmented reality (AR) techniques can help surgeons see the patient's internal anatomy in conjunction with laparoscopic video images. Method In this paper, we present an AR-assisted navigation system for liver resection based on a rigid stereoscopic laparoscope. The stereo image pairs from the laparoscope are used by an unsupervised convolutional network (CNN) framework to estimate depth and generate an intraoperative 3D liver surface. Meanwhile, 3D models of the patient's surgical field are segmented from preoperative CT images using V-Net architecture for volumetric image data in an end-to-end predictive style. A globally optimal iterative closest point (Go-ICP) algorithm is adopted to register the pre- and intraoperative models into a unified coordinate space; then, the preoperative 3D models are superimposed on the live laparoscopic images to provide the surgeon with detailed information about the subsurface of the patient's anatomy, including tumors, their resection margins and vessels. Results The proposed navigation system is tested on four laboratory ex vivo porcine livers and five operating theatre in vivo porcine experiments to validate its accuracy. The ex vivo and in vivo reprojection errors (RPE) are 6.04 ± 1.85 mm and 8.73 ± 2.43 mm, respectively. Conclusion and Significance Both the qualitative and quantitative results indicate that our AR-assisted navigation system shows promise and has the potential to be highly useful in clinical practice.
- Subjects :
- Laparoscopic surgery
Computer science
Swine
medicine.medical_treatment
Video Recording
Health Informatics
Stereoscopy
030218 nuclear medicine & medical imaging
Resection
law.invention
03 medical and health sciences
0302 clinical medicine
Deep Learning
Imaging, Three-Dimensional
law
Neoplasms
medicine
Image Processing, Computer-Assisted
Animals
Computer vision
Depth Perception
Augmented Reality
business.industry
Orientation (computer vision)
Iterative closest point
Navigation system
Reproducibility of Results
Laparoscopes
Computer Science Applications
Disease Models, Animal
Liver
Surgery, Computer-Assisted
Augmented reality
Laparoscopy
Artificial intelligence
business
Tomography, X-Ray Computed
030217 neurology & neurosurgery
Algorithms
Software
Subjects
Details
- ISSN :
- 18727565
- Volume :
- 187
- Database :
- OpenAIRE
- Journal :
- Computer methods and programs in biomedicine
- Accession number :
- edsair.doi.dedup.....188e3e07a427897dda0a2026b2c1bd73