In clinical imaging, the fundamental step is to extract useful data from images obtained by different sources and combining to form a single image called fused image to analyse and improve diagnosis. All image fusion techniques now a day rely majorly on non-fuzzy collections. As more qualms are taken into account as compared to non-fuzzy sets, fuzzy sets are better suited for medical image processing. We provide a method for effectively combining multimodal medical images in this study. As suggested, firstly, intuitionistic fuzzy images (IFIs) are obtained considering input source images into account. The optimal membership and non-membership function values are then derived for intuitionistic fuzzy entropy (IFE). After that, the IFIs are scrutinised using the fitness function, contrast visibility (CV). Then, Teaching–Learning-Based Optimization (TLBO) is utilised to maximise the fusion coefficients that are adjusted during the teaching stage and the learning phase of TLBO, allowing the weighted coefficients to naturally adapt to the fitness function. Finally, the fused image is acquired using the optimal coefficients. On various collections of source images, simulations are run, and the output findings are correlated to the most recent fusion techniques. The superiority of the suggested system is explained and supported. Edge-based image fusion (QAB/F), spatial frequency (SF), entropy (E), and other objective metrics are also used to assess how superior the fused image is.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fuzzy Set-Based Multimodal Medical Image Fusion with Teaching Learning-Based Optimization


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Sharma, Sanjay (Herausgeber:in) / Subudhi, Bidyadhar (Herausgeber:in) / Sahu, Umesh Kumar (Herausgeber:in) / Tirupal, T. (Autor:in) / Supriya, R. (Autor:in) / Devi, P. Uma (Autor:in) / Sunitha, B. (Autor:in)

    Kongress:

    International Conference on Robotics, Control, Automation and Artificial Intelligence ; 2022 November 24, 2022 - November 26, 2022



    Erscheinungsdatum :

    2023-11-18


    Format / Umfang :

    16 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Multimodal Medical Image Fusion Using the Sugeno Fuzzy Inference System

    Tirupal, T. / Shanavaj, K. / Venusri, M. et al. | Springer Verlag | 2023


    Fuzzy Logic Based Image Fusion

    T. J. Meitzler / D. Bednarz / E. J. Sohn et al. | NTIS | 2002


    Multimodal Features Fusion for Driver Fatigue Detection Based on CNN-GTN Learning

    Zhao, Shuaijie / Du, Aimin / Han, Yeyang et al. | IEEE | 2023


    Fuzzy-logic Based Information Fusion for Image Segmentation

    Aifanti, N. / Delopoulos, A. | British Library Conference Proceedings | 2005


    Fuzzy-logic based information fusion for image segmentation

    Aifanti, N. / Delopoulos, A. | IEEE | 2005