Abstract
We present a new method to solve the recognition and localisation problem of a surgical needle for robot-assisted laparoscopy. Based on the observation from a single monocular laparoscopic image, we propose a new modelling method to parametrise the full 3D pose of the surgical needle by constrained Degrees of freedom (DOFs) using only two generalised variables. To obtain effective image feedback for the modelling, a feature segmentation algorithm is introduced from probabilistic linear constraints in RGB colour space, constructed from typical laparoscopic images. An iterative algorithm using gradient descent rule is implemented to converge the computed needle's pose to its real one. Experiments demonstrate the feasibility of the proposed scheme using laparoscopic torso models.
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