Conference paper

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
Publication language:english
Original title:Design of HIFU Treatment Plans using Evolutionary Strategy
Title (cs):Využití evoluční strategie při návrhu HIFU operačních plánů
Pages:1568-1575
Proceedings:GECCO'18 Companion: Genetic and Evolutionary Computation Conference Companion
Conference:Genetic and Evolutionary Computations Conference 2018
Place:Kyoto, JP
Year:2018
URL:https://dl.acm.org/citation.cfm?doid=3205651.3208268
ISBN:978-1-4503-5764-7
DOI:10.1145/3205651.3208268
Publisher:Association for Computing Machinery
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Keywords
Evolutionary strategy, HIFU, treatment planning, k-Wave.
Annotation
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 %.
BibTeX:
@INPROCEEDINGS{
   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 = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso-8859-2?id=11696}
}

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