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  1. 1
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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  2. 2
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

    Published 2025
    “…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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  3. 3
    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images

    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

    Published 2016
    “…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. …”
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  4. 4
    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images

    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

    Published 2016
    “…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. …”
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  5. 5
    UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES

    UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES by MOHAMMAD SAMEER ALOUN

    Published 2022
    “…This thesis presents new methods to automate the segmentation of underwater coral reef images based on image processing techniques with the combination of color-texture features. …”
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    Thesis
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  6. 6
    Breast Ultrasound Automated ROI Segmentation with Region Growing

    Breast Ultrasound Automated ROI Segmentation with Region Growing by Lee, Lay-Khoon, Liew, Siau-Chuin

    Published 2015
    “…One of the simplest methods for image segmentation that is widely implemented in medical images is the region growing method. …”
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    Conference or Workshop Item
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  7. 7
    Image segmentation based on normalised cuts with clustering algorithm

    Image segmentation based on normalised cuts with clustering algorithm by Choong, Mei Yeen

    Published 2013
    “…With the approach applied in the normalised cuts based image segmentation, the constraint of using normalised cuts algorithm in image segmentation can be alleviated. …”
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  8. 8
    Multiregion segmentation of mammogram images by using parametric kernel graph cut algorithm / Nurhanani Abdul Rahim, Nor Farah Nabilah Mushtafa and Nadhirah Afiqah Zailan

    Multiregion segmentation of mammogram images by using parametric kernel graph cut algorithm / Nurhanani Abdul Rahim, Nor Farah Nabilah Mushtafa and Nadhirah Afiqah Zailan by Abdul Rahim, Nurhanani, Mushtaf, Nor Farah Nabilah, Zailan, Nadhirah Afiqah

    Published 2019
    “…Many methods are widely applied for image segmentation. …”
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  9. 9
    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation

    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

    Published 2011
    “…Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. …”
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  10. 10
    Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images

    Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images by Farzan, Ali, Ramli, Abdul Rahman, Mashohor, Syamsiah, Mahmud, Rozi

    Published 2010
    “…Segmentation of brain MRI is the core part in plenty of medical image processing methods. …”
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  11. 11
    Segmenting nodules of lung tomography image with level set algorithm and neural network

    Segmenting nodules of lung tomography image with level set algorithm and neural network by Chong, Soon Yee, Tan, Min Keng, Yeo, Kiam Beng, Mohd Yusof Ibrahim, Hao, Xiaoxi, Teo, Kenneth Tze Kin

    Published 2019
    “…The aim of this research is to develop an image segmentation algorithm for nodule detection in computed tomography (CT) image. …”
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  12. 12
    Image enhancement and segmentation on simultaneous latent fingerprint detection

    Image enhancement and segmentation on simultaneous latent fingerprint detection by Rozita, Mohd Yusof

    Published 2015
    “…Segmentation of 240 images is performed and compared with manual segmentation methods. …”
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  13. 13
    Image storage and retrieval using color quantization method

    Image storage and retrieval using color quantization method by Mandal, Koushik Kanti, Islam, Md. Rafiqul, Md. Sap, Mohd. Noor, Khatun, Fahmida, Reza, Md. Parvez

    Published 2005
    “…The image is segmented by our proposed segmentation algorithm, which uses the compact color descriptor .The result of the experiment shows that the developed segmentation algorithm produces better performances as compared with the existing segmentation algorithm. …”
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  14. 14
    A Hybrid Active Contour and Artificial Bee Colony Algorithm for Segmenting Mixed-Meal Food Images (S/O: 13239)

    A Hybrid Active Contour and Artificial Bee Colony Algorithm for Segmenting Mixed-Meal Food Images (S/O: 13239) by Harun, Nor Hazlyna, Mahmuddin, Massudi, Harun, Hazaruddin

    Published 2020
    “…This method is adopted for food image segmentation, wherein the boundaries of the foods in an image are the objects of interest. …”
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    Monograph
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  15. 15
    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation

    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation by Li, Min, Huang, Tinglei, Zhu, Gangqiang

    Published 2008
    “…Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. …”
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  16. 16
    Enhanced Clustering Algorithms For Gray-Scale Image Segmentation

    Enhanced Clustering Algorithms For Gray-Scale Image Segmentation by Siddiqui, Fasahat Ullah

    Published 2012
    “…The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. …”
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  17. 17
    Using a novel algorithm in ultrasound images to detect renal stones

    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…In this paper, three essential segmentation algorithms, namely Fuzzy C-means, K-means, and Expectation–Maximization algorithms, are proposed for the identification of renal stone in kidney ultrasound images. …”
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  18. 18
    Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm

    Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm by Abdurrahim, Salem Hamed

    Published 2004
    “…The watershed segmentation algorithm is a very powerful segmentation tool, but it also has difficulty in segmenting MR images due to noise and shading effect present. …”
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  19. 19
    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm

    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm by Alomoush W., Alrosan A., Norwawi N., Alomari Y., Albashish D., Almomani A., Alqahtani M.

    Published 2024
    journal::journal article
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  20. 20
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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