Faculty of Information Technology, BUT

Publication Details

Design of HIFU Treatment Plans using Evolutionary Strategy

ČUDOVÁ Marta, TREEBY Bradley E. and JAROŠ Jiří. Design of HIFU Treatment Plans using Evolutionary Strategy. In: GECCO'18 Companion: Genetic and Evolutionary Computation Conference Companion. Kyoto: Association for Computing Machinery, 2018, pp. 1568-1575. ISBN 978-1-4503-5764-7. Available from: https://dl.acm.org/citation.cfm?doid=3205651.3208268
Czech title
Využití evoluční strategie při návrhu HIFU operačních plánů
Type
conference paper
Language
english
Authors
Čudová Marta, Ing. (DCSY FIT BUT)
Treeby Bradley E. (UCL)
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT)
URL
Keywords
Evolutionary strategy, HIFU, treatment planning, k-Wave.
Abstract
High Intensity Focused Ultrasound (HIFU) is an emerging technique for non-invasive cancer treatment where malignant tissue is destroyed by thermal ablation. Since one ablation only allows a small region of tissue to be destroyed, a series of ablations has to be conducted to treat larger volumes. To maximize the treatment outcome and prevent injuries such as skin burns, complex preoperative treatment planning is carried out to determine the focal position and sonication time for each ablation. Here, we present an evolutionary strategy to design HIFU treatment plans using a map of patient specific material properties and a realistic thermal model. The proposed strategy allows high-quality treatment plans to be designed, with the average volume of mistreated and under-treated tissue not exceeding 0.1 %.
Published
2018
Pages
1568-1575
Proceedings
GECCO'18 Companion: Genetic and Evolutionary Computation Conference Companion
Conference
Genetic and Evolutionary Computations Conference 2018, Kyoto, JP
ISBN
978-1-4503-5764-7
Publisher
Association for Computing Machinery
Place
Kyoto, JP
DOI
BibTeX
@INPROCEEDINGS{FITPUB11696,
   author = "Marta \v{C}udov\'{a} and E. Bradley Treeby and Ji\v{r}\'{i} Jaro\v{s}",
   title = "Design of HIFU Treatment Plans using Evolutionary Strategy",
   pages = "1568--1575",
   booktitle = "GECCO'18 Companion: Genetic and Evolutionary Computation Conference Companion",
   year = 2018,
   location = "Kyoto, JP",
   publisher = "Association for Computing Machinery",
   ISBN = "978-1-4503-5764-7",
   doi = "10.1145/3205651.3208268",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11696"
}
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