Abstract
The detection of surgical instruments in real time is one of the most challenging problems in retinal microsurgery operations. The instrument’s deformable shape, the presence of its shadow, and the illumination variations are the main contributors for such challenge. A new approach for the detection of the tip of the surgical tool is proposed, which can handle the shape deformation, and the presence of the its shadow or the presence of blood vessels. The approach starts by segmenting the tool-like objects using the L*a*b color model. One of these segments is selected as the target tool based on tool’s shaft model. The probabilistic Hough transform was used to get the structural information which can guide us to optimize the best possible candidates’ locations to fit the tool model. The detected tool tip and its slope are propagated between the frames in the images sequence. Experimental results demonstrate the high accuracy of this technique in addition to achieve the real time requirements.
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