Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery | Zendy

Jia Gu | Zendy; Rolf Wolters | Zendy; Ulf Gustafsson | Zendy

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Temporal Matching in Endoscopic Images for Remote-Controlled Robotic Surgery

Author(s) -

Jia Gu,

Rolf Wolters,

Ulf Gustafsson

Publication year - 2009

Publication title -

international journal of telemedicine and applications

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.363

H-Index - 27

eISSN - 1687-6423

pISSN - 1687-6415

DOI - 10.1155/2009/627625

Subject(s) - computer science , matching (statistics) , segmentation , artificial intelligence , boundary (topology) , computer vision , frame (networking) , tracking (education) , stage (stratigraphy) , template matching , string (physics) , image (mathematics) , pattern recognition (psychology) , medicine , geology , mathematics , pathology , psychology , mathematical analysis , telecommunications , pedagogy , paleontology , mathematical physics

Temporal matching is applied in the frame of the formation of high-level entities in remote-controlled robotic surgery. The objective is to track tumor boundaries over time to improve the segmentation stage in each image of the sequence to facilitate the tracking and localization of the tumor. It makes use of an attributed string matching technique to find the correspondence between tumor boundaries over time. Relationships are then exploited to reconstitute the tumor boundaries and remove the inconsistencies coming from the detection errors. Input data are free form shapes of different length representing the tumor boundary, extracted at a previous stage.

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