Comput. Biol. Med. - Coverage planning in computer-assisted ablation based on Genetic Algorithm.

Tópicos

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Resumo

An ablation planning system plays a pivotal role in tumor ablation procedures, as it provides a dry run to guide the surgeons in a complicated anatomical environment. Over-ablation, over-perforation or under-ablation may result in complications during the treatments. An optimal solution is desired to have complete tumor coverage with minimal invasiveness, including minimal number of ablations and minimal number of perforation trajectories. As the planning of tumor ablation is a multi-objective problem, it is challenging to obtain optimal covering solutions based on clinicians experiences. Meanwhile, it is effective for computer-assisted systems to decide a set of optimal plans. This paper proposes a novel approach of integrating a computational optimization algorithm into the ablation planning system. The proposed ablation planning system is designed based on the following objectives: to achieve complete tumor coverage and to minimize the number of ablations, number of needle trajectories and over-ablation to the healthy tissue. These objectives are taken into account using a Genetic Algorithm, which is capable of generating feasible solutions within a constrained search space. The candidate ablation plans can be encoded in generations of chromosomes, which subsequently evolve based on a fitness function. In this paper, an exponential weight-criterion fitness function has been designed by incorporating constraint parameters that were reflective of the different objectives. According to the test results, the proposed planner is able to generate the set of optimal solutions for tumor ablation problem, thereby fulfilling the aforementioned multiple objectives.

Resumo Limpo

ablat plan system play pivot role tumor ablat procedur provid dri run guid surgeon complic anatom environ overabl overperfor underabl may result complic treatment optim solut desir complet tumor coverag minim invas includ minim number ablat minim number perfor trajectori plan tumor ablat multiobject problem challeng obtain optim cover solut base clinician experi meanwhil effect computerassist system decid set optim plan paper propos novel approach integr comput optim algorithm ablat plan system propos ablat plan system design base follow object achiev complet tumor coverag minim number ablat number needl trajectori overabl healthi tissu object taken account use genet algorithm capabl generat feasibl solut within constrain search space candid ablat plan can encod generat chromosom subsequ evolv base fit function paper exponenti weightcriterion fit function design incorpor constraint paramet reflect differ object accord test result propos planner abl generat set optim solut tumor ablat problem therebi fulfil aforement multipl object

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