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Pareto front vs. Weighted sum for automatic trajectory planning of deep brain stimulation

Abstract : Preoperative path planning for Deep Brain Stimulation (DBS) is a multi-objective optimization problem consisting in searching the best compromise between multiple placement constraints. Its automation is usually addressed by turning the problem into mono objective thanks to an aggregative approach. However,despite its intuitiveness,this approach is known for its incapacity to find all optimal solutions. In this work,we introduce an approach based on multi objective dominance to DBS path planning. We compare it to a classical aggregative weighted sum of the multiple constraints and to a manual planning thanks to a retrospective study performed by a neurosurgeon on 14 DBS cases. The results show that the dominance-based method is preferred over manual planning,and covers a larger choice of relevant optimal entry points than the traditional weighted sum approach which discards interesting solutions that could be preferred by surgeons. © Springer International Publishing AG 2016.
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Contributor : Laurent Jonchère Connect in order to contact the contributor
Submitted on : Thursday, December 15, 2016 - 3:14:17 PM
Last modification on : Wednesday, September 14, 2022 - 10:20:04 AM

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N. Hamzé, J. Voirin, P. Collet, Pierre Jannin, C. Haegelen, et al.. Pareto front vs. Weighted sum for automatic trajectory planning of deep brain stimulation. 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, Oct 2016, Athens, Greece. pp.534--541, ⟨10.1007/978-3-319-46720-7_62⟩. ⟨hal-01417319⟩



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