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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  2. 2
    Image segmentation based on normalised cuts with clustering algorithm

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

    Published 2013
    “…Evaluation of c -means and fuzzy c-means clustering algorithm with normalised cuts image segmentation on various kinds of images has been carried out. …”
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  3. 3
    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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  4. 4
    Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation.

    Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation. by Mohammad Khusairi, Osman, Mohd Yusoff, Mashor, Prof. Dr., Hasnan, Jaafar

    Published 2013
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  5. 5
    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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  6. 6
    Unsupervised segmentation technique for acute leukemia cells using clustering algorithms

    Unsupervised segmentation technique for acute leukemia cells using clustering algorithms by Harun, Nor Hazlyna, Abdul Nasir, Aimi Salihah, Mashor, Mohd Yusoff, Hassan, Rosline

    Published 2015
    “…Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image.In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. …”
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  7. 7
    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor

    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor by Abu Mangshor, Nur Nabilah

    Published 2010
    “…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. …”
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  8. 8
    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images

    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images by Jabar F.H.A., Ismail W., Salam R.A., Hassan R.

    Published 2024
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  9. 9
    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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  10. 10
    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
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    journal::journal article
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  11. 11
    MRI segmentation of medical images using FCM with initialized class centers via genetic algorithm

    MRI segmentation of medical images using FCM with initialized class centers via genetic algorithm by Balafar, Mohammad Ali, Ramli, Abdul Rahman, Saripan, M. Iqbal, Mahmud, Rozi, Mashohor, Syamsiah, Balafar, Hakimeh

    Published 2008
    “…Image segmentation is a critical stage in many computer vision and image process applications. …”
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  12. 12
    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
    “…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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  13. 13
    Cluster approach for auto segmentation of blast in acute leukimia blood slide images

    Cluster approach for auto segmentation of blast in acute leukimia blood slide images by N. H., Harun, Mohd Yusoff, Mashor, Prof. Dr., H., Rosline

    Published 2011
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  14. 14
    Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application

    Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application by Maliki, Mohamad Nansah, Abu Bakar Al-Attas, Syed Abdul Rahman

    Published 2004
    “…Fuzzy-based clustering algorithm is becoming popular in image processing, especially in image segmentation. …”
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  15. 15
    Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering

    Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering by Abang Mohd Arif Anaqi, Abang Isa

    Published 2021
    “…This study aims to develop an automatic segmentation by utilizing clustering algorithm for acute ischemic stroke lesion identification. …”
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  16. 16
    Blood cell image segmentation using unsupervised clustering techniques

    Blood cell image segmentation using unsupervised clustering techniques by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina

    Published 2009
    “…The aim of our research is to develop an effective algorithm for segmentation of the blood cell images. …”
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  17. 17
    Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI

    Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI by Abang Mohd Arif Anaqi, Abang Isa, Kuryati, Kipli, Ahmad Tirmizi, Jobli, Muhammad Hamdi, Mahmood, Siti Kudnie, Sahari, Aditya Tri, Hernowo, Sinin, Hamdan

    Published 2021
    “…This paper presented an automated segmentation algorithm on diffusion-weighted magnetic resonance imaging (DW-MRI) image utilizing pseudo-colour conversion and K-means clustering techniques. …”
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  18. 18
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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  19. 19
    Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images

    Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images by Jabar, FHA, Ismail, W, Salam, RA, Hassan, R

    Published 2024
    “…This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. …”
    Proceedings Paper
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  20. 20
    Cluster validity of Xie and Beni and the partition coefficient indexes for fuzzy c-means clustering / Nor Azrin Ahmad Mustaffa

    Cluster validity of Xie and Beni and the partition coefficient indexes for fuzzy c-means clustering / Nor Azrin Ahmad Mustaffa by Ahmad Mustaffa, Nor Azrin

    Published 2010
    “…Under Image Processing, there is Image Segmentation. Image Segmentation is a subset of an expansive field of computer vision which deals with partition an image into meaningful regions with respect to a particular application. …”
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