Coverage planning in computer-assisted ablation based on Genetic Algorithm.
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 t...
| Publicado en: | Computers in Biology & Medicine Vol. 49; pp. 36 - 46 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103822558&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103822558 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00104825 JC2 jtl: Computers in Biology & Medicine issn: 00104825 maglogo: N pubinfo: dt: 2014 vid: 49 pid: 82545 pub: Elsevier B.V. place: Philadelphia, Pennsylvania artinfo: ui: 103822558 NLM24736202 2012578697 10.1016/j.compbiomed.2014.03.004 NLM24736202 103822558 ppf: 36 ppct: 10 formats: tig: atl: Coverage planning in computer-assisted ablation based on Genetic Algorithm. aug: au: Ren, Hongliang Guo, Weian Sam Ge, Shuzhi Lim, Wancheng affil: Department of Biomedical Engineering, National University of Singapore, Singapore. Electronic address: ren@nus.edu.sg. sug: subj: Ablation Techniques Methods Algorithms Models, Biological Therapy, Computer Assisted Methods Computer Simulation Neoplasms Radiography Neoplasms Surgery Swine Tomography, X-Ray Computed Animal Studies ab: 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 clinician׳s 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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