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Erschienen in:
2015 | OriginalPaper | Buchkapitel
A Merging Model Reconstruction Method for Image-Guided Gastroscopic Biopsy
verfasst von : Juan He, Yinhong Zhao, Jiquan Liu, Bin Wang, Huilong Duan
Erschienen in: Advances in Image and Graphics Technologies
Verlag: Springer Berlin Heidelberg
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Tattooing and Argon plasma coagulation (APC) are used for gastroscopic biopsy traditionally. To overcome the invasive issues of tattooing and APC, we proposed an image-guided gastroscopic biopsy system (IGGBS) to guide endoscopist in retargeting previous biopsy sites in the follow-ups non-invasively. In this paper, a model merging method is proposed to improve the IGGBS’s accuracy. The method reconstructs local realistic model based on gastroscopic image sequences during procedure, then the local model is merged with the pre-operative model in real-time. As a consequence, the merging model is used in IGGBS to navigate endoscopist to retarget biopsy sites, which provides the endoscopist with a confident 3D region around the endoscope camera site and a measure of the reconstruction precision. As the experimental result shows, the root mean square target registration error of IGGBS using merging model is 9.5 mm, which is close to the conventional biopsy tattooing method (about 1cm).