RT Conference Proceedings
T1 Cuckoo search algorithm for border reconstruction of medical images with rational curves
A1 Gálvez, Akemi
A1 Fister, Iztok
A1 Fister, Iztok
A1 Osaba, Eneko
A1 Ser, Javier Del
A1 Iglesias, Andrés
A2 Tan, Ying
A2 Shi, Yuhui
A2 Niu, Ben
AB Border reconstruction is a key technology in medical image processing, where it is applied to identify and separate different tissues, organs, and tumors in diagnostic procedures. The classical approaches for this problem are based on either linear or polynomial functions to describe the border of the region of interest. However, little effort has been devoted to the more powerful case of rational functions, which extend the polynomial case by including extra degrees of freedom (the weights). As a consequence, rational functions are more difficult to compute. In this paper, we solve the problem by applying a nature-inspired swarm intelligence method called cuckoo search algorithm. The method is applied to two illustrative examples of medical images with satisfactory results.
PB Springer Verlag
SN 9783030263683
SN 0302-9743
YR 2019
FD 2019
LK https://hdl.handle.net/11556/2692
UL https://hdl.handle.net/11556/2692
LA eng
NO Gálvez , A , Fister , I , Fister , I , Osaba , E , Ser , J D & Iglesias , A 2019 , Cuckoo search algorithm for border reconstruction of medical images with rational curves . in Y Tan , Y Shi & B Niu (eds) , Advances in Swarm Intelligence - 10th International Conference, ICSI 2019, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 11655 LNCS , Springer Verlag , pp. 320-330 , 10th International Conference on Swarm Intelligence, ICSI 2019 , Chiang Mai , Thailand , 26/07/19 . https://doi.org/10.1007/978-3-030-26369-0_30
NO conference
NO Publisher Copyright: © Springer Nature Switzerland AG 2019.
NO zon 2020 program), #TIN2017-89275-R (Spanish Research Agency, AEI/UE FEDER), P2-0057 & P2-0041 (Slovenian Research Agency) and EMAITEK (Basque Government). Work supported by projects: PDE-GIR #778035 (EU Horizon 2020 program), #TIN2017-89275-R (Spanish Research Agency, AEI/UE FEDER), P2-0057 & P2-0041 (Slovenian Research Agency) and EMAITEK (Basque Government). Acknowledgements. Work supported by projects: PDE-GIR #778035 (EU Hori-
DS TECNALIA Publications
RD 28 jul 2024