Multimodal Medical Images using Rigid Iconic Registration based on Flower Pollination Algorithm and Butterfly Optimization Algorithm - Université Polytechnique des Hauts-de-France Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Multimodal Medical Images using Rigid Iconic Registration based on Flower Pollination Algorithm and Butterfly Optimization Algorithm

Résumé

One of the numerous challenges of modern image processing is image registration. Information from many images often emerges in slightly different forms and is highly compatible. Spatial alignment is crucial to merge essential and valuable information from several images properly. The term "registration" describes this procedure. Find a transformation that results in a model that closely resembles the reference image [1].Mainly, this work is concerned with implementing two optimization algorithms: the Flower Pollination Algorithm (FPA) and the Butterfly Optimization Algorithm (BOA). To measure the efficacy of these methods, we compare the transformed image to the original by computing the mutual information between the two. The effectiveness of these methods was assessed using SSIM, EQM, and MI measures. Results from the experiments indicate that the BOA outperforms the FPA.
Fichier principal
Vignette du fichier
NTIC22.Sara.Babahenini.final.pdf (591 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04109397 , version 1 (05-06-2023)

Identifiants

Citer

Sarra Babahenini, Fella Charif, Abdelmalik Taleb-Ahmed. Multimodal Medical Images using Rigid Iconic Registration based on Flower Pollination Algorithm and Butterfly Optimization Algorithm. 2022 2nd International Conference on New Technologies of Information and Communication (NTIC), Dec 2022, Mila, Algeria. pp.1-6, ⟨10.1109/NTIC55069.2022.10100397⟩. ⟨hal-04109397⟩
24 Consultations
21 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More