An endoscopic structured light system using multispectral detection

• Published in: International journal for computer assisted radiology and surgery 2015-12, Vol.10 (12), p.1941-1950
• Main Authors: Lin, Jianyu, Clancy, Neil T., Elson, Daniel S.
• Format: Article
• Language: English
• Subjects: Algorithms; Computer Imaging; Computer Science; Endoscopy - methods; Feasibility Studies; Health Informatics; Humans; Image Interpretation, Computer-Assisted - methods; Imaging; Lighting - methods; Medicine; Medicine & Public Health; Original Article; Pattern Recognition and Graphics; Phantoms, Imaging; Radiology; Sensitivity and Specificity; Surgery; Vision
• ISSN: 1861-6410; 1861-6429
• DOI: 10.1007/s11548-015-1264-4

Purpose In clinical examinations, the tissue surface topology is an important feature for detecting the tissue pathology and implementing augmented reality. We have previously presented a miniaturised structured light (SL) system for recovery of tissue surface shape in minimally invasive surgery (MIS), based on a flexible multispectral structured illumination probe (1.9 mm diameter) (Clancy et al. in Biomed Opt Express 2(11):3119–3128, 2011 . doi: 10.1364/BOE.2.003119 ). This paper reports further hardware and analytical developments to improve the light pattern decoding result and increase the reconstruction accuracy. Methods The feasibility of using an 8-band multispectral camera with higher pattern-colour discrimination ability than normal RGB camera in this system was studied. Additionally, the “normalised cut” algorithm was investigated to improve pattern segmentation. Results The whole SL system was evaluated by phantom and in vivo experiments. Higher pattern identification performance than that of an RGB camera was recorded by using the multispectral camera (average precision >97 %, average sensitivity >62 %). An average of 0.88 ± 0.67 mm reconstruction error was achieved using the proposed pattern decoding method on a heart phantom at a working distance of approximately 10 cm. Conclusions The experiment showed the superiority of the multispectral camera over the RGB camera in the spot identification step. The proposed pattern decoding algorithm underwent evaluations using different experiments, showing that it provided promising reconstruction results. The potential of using this system in MIS environments has been demonstrated.