Fly algorithm: Difference between revisions

Revision as of 15:43, 4 November 2016

Revision as of 15:44, 4 November 2016

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Another application field of the Fly Algorithm is reconstruction for [[emission Tomography]] in [[nuclear medicine]]. The Fly algorithm has been successfully applied in [[single-photon emission computed tomography]]<ref>{{cite conference |title=Fully Three-Dimensional Tomographic Evolutionary Reconstruction in Nuclear Medicine|last1=Bousquet|first1=Aurélie|last2=Louchet|first2=Jean-Marie|last3=Rocchisani|first3=Jean|publisher=Springer, Heidelberg|conference=Proceedings of the 8th international conference on Artificial Evolution (EA’07)|pages=231–242|date=Oct 2007|doi=10.1007/978-3-540-79305-2_20|isbn=978-3-540-79304-5|___location=Tours, France|volume=4926|book-title=Lecture Notes in Computer Science|url=http://jean.louchet.free.fr/publis/EA07Bousquet.pdf|}}</ref> and [[positron emission tomography]]<ref>{{cite conference |title=Artificial evolution for 3D PET reconstruction|last1=Vidal|first1=Franck P.|last2=Lazaro-Ponthus|first2=Delphine|last3=Legoupil|first3=Samuel|first4=Jean|first5=Évelyne|first6=Jean-Marie|last4=Louchet|last5=Lutton|last6=Rocchisani|publisher=Springer, Heidelberg|conference=Proceedings of the 9th international conference on Artificial Evolution (EA’09)|pages=37–48|date=Oct 2009|doi=10.1007/978-3-642-14156-0_4|isbn=978-3-642-14155-3|___location=Strasbourg, France|volume=5975|book-title=Lecture Notes in Computer Science|url=http://fly4pet.fpvidal.net/pdf/Vidal2009EA.pdf|}}</ref>

<ref>{{cite conference |title=PET reconstruction using a cooperative coevolution strategy in LOR space|last1=Vidal|first1=Franck P.|last2=Louchet|first2=Jean|last3=Lutton|first3=Évelyne|last4=Rocchisani|first4=Jean-Marie|publisher=IEEE|conference=Medical Imaging Conference (MIC)|pages=3363–3366|date=Oct-Nov 2009|doi=10.1109/NSSMIC.2009.5401758|___location=Orlando, Florida|book-title=IEEE Nuclear Science Symposium Conference Record (NSS/MIC), 2009|}}</ref>. Here, each fly is considered a photon emitter and its fitness is based on the conformity of the simulated illumination of the sensors with the actual pattern observed on the sensors. Within this application, the fitness function has been re-defined as the (positive or negative_ contribution of the fly considered, to the global conformity of the simulated illumination with the actual one ("marginal fitness" or "marginal evaluation")<ref>{{cite conference |title=New genetic operators in the Fly algorithm: application to medical PET image reconstruction|last1=Vidal|first1=Franck P.|last2=Louchet|first2=Jean|last4=Lutton|first4=Évelyne|last3=Rocchisani|first3=Jean-Marie|publisher=Springer, Heidelberg|conference=European Workshop on Evolutionary Computation in Image Analysis and Signal Processing (EvoIASP’10)|pages=292–301|date=Apr 2010|doi=10.1007/978-3-642-12239-2_30|isbn=978-3-642-12238-5|___location=Istanbul, Turkey|volume=6024|book-title=Lecture Notes in Computer Science|url=http://fly4pet.fpvidal.net/pdf/Vidal2010EvoIASP.pdf|}}</ref><ref>{{cite conference |title=Threshold selection, mitosis and dual mutation in cooperative co-evolution: Application to medical 3D tomography|last1=Vidal|first1=Franck P.|last2=Lutton|first2=Évelyne|last3=Louchet|first3=Jean|last4=Rocchisani|first4=Jean-Marie|publisher=Springer Berlin / Heidelberg|conference=Parallel Problem Solving from Nature - PPSN XI|pages=414–423|date=Sep 2010|doi=10.1007/978-3-642-15844-5_42|isbn=978-3-642-15843-8|___location=Kraków, Poland|volume=6238|book-title=Lecture Notes in Computer Science|url=http://www.fpvidal.net/fly4pet/pdf/Vidal2010PPSN.pdf|}}</ref>.

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