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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 name=Bousquet2007EA>{{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 name=Vidal2009EA>{{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 name=Vidal2009MIC>{{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 name=Vidal2010EvoIASP>{{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>. In <ref name=Abbood2017SWEVO>>{{cite journal |title=Voxelisation in the 3-D Fly Algorithm for PET|last1=Ali Abbood|first1=Zainab|last2=Lavauzelle|first2=Julien|last3=Lutton|first3=Évelyne|last4=Rocchisani|first4=Jean-Marie|last5=Louchet|first5=Jean|last6=Vidal|first36Franck P.|publisher=Elsevier|page=???|date=2017|doi=10.1016/j.swevo.2017.04.001|issn=2210-6502|volume=???|issue=???|journal=Swarm and Evolutionary Computation|url=http://fly4pet.fpvidal.net/pdf/Abbood2017SWEVO.pdf|}}</ref>
More recently it has been used in digital art to generate mosaic-like images or spray paint<ref name=Abbood2017EvoIASP>{{cite conference |title=Evolutionary Art Using the Fly Algorithm|last1=Ali Abbood|first1=Zainab|last2=Amlal|first2=Othman|last3=Vidal|first3=Franck P.|publisher=Springer|conference=Applications of Evolutionary Computation (EvoApplications 2017)|pages=455-470|date=Apr 2017|doi=10.1007/978-3-319-55849-3_30|___location=Amsterdam, The Netherlands|volume=10199|book-title=Lecture Notes in Computer Science|url=http://fly4pet.fpvidal.net/pdf/Abbood017EvoIASP.pdf|}}</ref>.
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