title: Comparison of two algorithms for the application of real-time image mosaicking in neuroendoscopy.
abstract: OBJECTIVE
  Neuroendoscopy is used more and more frequently in neurosurgical procedures and has become an important tool in the neurosurgical armamentarium. However, the main restriction of neuroendoscopy is the limited field of view. A better overview of the area of interest would increase surgical safety and decrease procedure-related morbidity rates. In the present study, the authors aimed to improve this restriction by using and comparing two algorithms to create endoscopic panoramic images, which increase the field of view during neuroendoscopic procedures.
  
  
  METHODS
  Different endoscopic methods with or without a stand and with linear or circular endoscope movements were performed in cadaveric ventricles. Video of the endoscopy was used to create image mosaics of the lateral ventricle with the help of the Kourogi or LogSearch (LS) algorithm. In the LS algorithm, different template sizes were used. Three observers graded the quality of the image mosaic in terms of usefulness in surgery. The fastest frame rate was 3-4 frames/second.
  
  
  RESULTS
  The LS algorithm with a larger template size showed significantly better results for the creation of image mosaics than the Kourogi algorithm in linear endoscopic movement with or without a stand. In circular endoscopic movements, the results seemed to be better with the LS algorithm but were not significantly different from those obtained with the Kourogi algorithm. In summary, image quality in the experimental paradigms was satisfying.
  
  
  CONCLUSIONS
  Results in the study showed that the creation of image mosaics is possible and reliable with the featured algorithms. Image mosaicking is an applicable device for neuroendoscopy and can increase the field of view during endoscopic procedures. Its use can increase the safety and the field of application of neuroendoscopy. However, faster frame rates will be required to create a smooth image for practical use during surgery.
authors.affiliation: Department of Neurosurgery, Klinikum Duisburg, SANA Kliniken, Academic Teaching Hospital of University Essen-Duisburg; and.
authors.forename: Kay Niklas
authors.initials: KN
authors.lastname: Liebig
authors.forename: Homajoun
authors.initials: H
authors.lastname: Maslehaty
authors.forename: Athanasios K
authors.initials: AK
authors.lastname: Petridis
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Konen
authors.forename: Martin
authors.initials: M
authors.lastname: Scholz
mesh_terms: D000465:Algorithms; D002102:Cadaver; D002552:Cerebral Ventricles / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D044583:Neuroendoscopy / Q000379:methods*; D015203:Reproducibility of Results; D013997:Time Factors
keywords: LS = LogSearch; algorithm; fps = frames per second; image mosaic; neuroendoscopy; optical flow