Pareto front vs. weighted sum for automatic trajectory planning of Deep Brain Stimulation

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.

N. Hamze , J. Voirin , P. Collet , P. Jannin , C. Haegelen , C. Essert

Medical Image Computing and Computer Assisted Intervention (MICCAI'16) , Volume 9900 , page 534-541 - 2016

@Inproceedings{4-HVCJ16,
 author = {Hamze, N. and Voirin, J. and Collet, P. and Jannin, P. and Haegelen, C. and Essert, C.},
 title = {Pareto front vs. weighted sum for automatic trajectory planning of Deep Brain Stimulation},
 booktitle  = {Medical Image Computing and Computer Assisted Intervention (MICCAI'16)},
 series = {LNCS},
 volume = {9900},
 pages = {534-541},
 month = {Oct},
 year = {2016},
 publisher = {Springer},
 note = {(CORE rank A)},
 type = {Selective conference},
 doi = {10.1007/978-3-319-46720-7_62},
 x-international-audience = {Yes},
 x-language = {EN},
 url = {http://publis.icube.unistra.fr/4-HVCJ16}
}