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by Keyword: Motion compensation


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Aviles, A. I., Sobrevilla, P., Casals, A., (2014). An approach for physiological motion compensation in robotic-assisted cardiac surgery Experimental & Clinical Cardiology , 20, (11), 6713-6724

The lack of physiological motion compensation is a major problem in robotic-assisted cardiac surgery. Since the heart is beating while the surgeon carried out the procedure, dexterity of the surgeon’s and precision are compromised. Due to the operative space and the visibility of the surgical field are reduced, the most practical solution is the use of computer vision techniques. The lack of efficiency and robustness of the existing proposals make physiological motion compensation to be considered an open problem. In this work a novel solution to solve this problem based on the minimization of an energy functional is presented. It is described in the three-dimensional space using the l1−regularized optimization class in which cubic b-splines are used to represent the changes produced on the heart surface. Moreover, the logarithmic barrier function is applied to create an approximation of the total energy in order to avoid its non-differentiability. According to the results, this proposal is able to deal with complex deformations, requires a short computational time and gives a small error.

Keywords: Beating heart surgery, Image analysis, Motion compensation


Aviles, A. I., Sobrevilla, P., Casals, A., (2014). In search of robustness and efficiency via l1− and l2− regularized optimization for physiological motion compensation International Journal of Medical, Health, Pharmaceutical and Biomedical Engineering XII International Conference on Agricultural, Biological and Ecosystems Sciences (ICABES 2014) , World Academy of Science, Engineering and Technology (WASET) (Geneva, Switzerland) 8, 501-506

Compensating physiological motion in the context of minimally invasive cardiac surgery has become an attractive issue since it outperforms traditional cardiac procedures offering remarkable benefits. Owing to space restrictions, computer vision techniques have proven to be the most practical and suitable solution. However, the lack of robustness and efficiency of existing methods make physiological motion compensation an open and challenging problem. This work focusses on increasing robustness and efficiency via exploration of the classes of l1- and l2-regularized optimization, emphasizing the use of explicit regularization. Both approaches are based on natural features of the heart using intensity information. Results pointed out the l1-regularized optimization class as the best since it offered the shortest computational cost, the smallest average error and it proved to work even under complex deformations.

Keywords: Motion Compensation, Optimization, Regularization, Beating Heart Surgery, Ill-posed problem