A global approach for automatic fibroscopic video mosaicing in minimally invasive diagnosis.
Recent developments in bio-photonics have called for the need of bringing cellular and molecular imaging modalities to an in vivo--in situ setting to allow for real-time tissue characterization and functional assessment. Before such techniques can be used effectively in routine clinical environments, it is necessary to address the visualization requirement for linking point based optical biopsy to large area tissue visualization. This paper presents a novel approach for fibered endoscopic video mosaicing that permits wide region tissue visualization. A feature-based registration method is used to register the frames of the endoscopic video sequence by taking into account the characteristics of fibroscopic imaging such as non-linear lens distortion and high-frequency fiber optic facet pattern. The registration is combined with an efficient optimization scheme in order to align all input frames in a globally consistent way. An evaluation on phantom and ex vivo tissue images allowing free-hand camera motion is presented.
Atasoy
Selen
S
Department of Computing, Imperial College London. catasoy@imperial.ac.uk
Noonan
David P
DP
Benhimane
Selim
S
Navab
Nassir
N
Yang
Guang-Zhong
GZ
D000465:Algorithms; D001185:Artificial Intelligence; D019723:Endoscopes; D004724:Endoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018715:Microscopy, Video / Q000379:methods*; D019060:Minimally Invasive Surgical Procedures / Q000295:instrumentation / Q000379:methods; D055100:Optical Fibers; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000295:instrumentation / Q000379:methods