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  1. 1
    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim

    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim by Ibrahim, Shafaf

    Published 2015
    “…The study revealed that very high pixel detection is noticeable in PSG algorithm which leads to over-segmentation in the tumor areas, and indirectly affected the segmentation accuracy. …”
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  2. 2
    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
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  3. 3
    Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach

    Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach by Vadiveloo, Mogana

    Published 2020
    “…Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. …”
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  4. 4
    Red blood cell segmentation using masking and watershed algorithm: A preliminary study

    Red blood cell segmentation using masking and watershed algorithm: A preliminary study by Johan, Mohamad Sharif, M. F., Miswan, Md Asri, Ngadi, Md Sah, Hj Salam, Muhammad Mahadi, Abdul Jamil

    Published 2012
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  5. 5
    Evaluation of automated phonetic labeling and segmentation for dyslexic children’s speech

    Evaluation of automated phonetic labeling and segmentation for dyslexic children’s speech by Husni, Husniza, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2013
    “…This is due to the highly phonetically similar reading errors produced when they read that have affected automatic speech recognition (ASR).In this work, experiments were performed using a specifically designed ASR to force-align the read speech and produce the labels and segmentations automatically.The CSLU toolkit’s force alignment algorithm has been employed to measure their performances.Selected speech data of dyslexic children’s reading in Malay were fed to the algorithm as input and the evaluation resulted in 95% agreement on phonetic labeling and only 65% on segmentation with respect to the manual ones.…”
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  6. 6
    Stereo Matching Algorithm Based On Per Pixel Difference Adjustment, Iterative Guided Filter And Graph Segmentation

    Stereo Matching Algorithm Based On Per Pixel Difference Adjustment, Iterative Guided Filter And Graph Segmentation by Hamzah, Rostam Affendi, Ibrahim, Haidi, Abu Hassan, Anwar Hasni

    Published 2017
    “…The undirected graph segmentation is used at the last stage in order to smoothen the low textured areas. …”
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  7. 7
    Segmentation of MRI Prostate Images using Gaussian Mixture Models (GMMs)

    Segmentation of MRI Prostate Images using Gaussian Mixture Models (GMMs) by Roslee, Nur Aqilah

    Published 2016
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  8. 8
    Supervised retinal vessel segmentation based on neural network using broader aging dataset

    Supervised retinal vessel segmentation based on neural network using broader aging dataset by Che Azemin, Mohd Zulfaezal, Abd Hamid, Fadilah, Mohd Tamrin, Mohd Izzuddin, Muhamad Amin, Anang Hudaya

    Published 2014
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  9. 9
    Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting by Mansor, R., Kasim, M.M., Othman, M.

    Published 2020
    “…This paper modifies the classical fuzzy time series (FTS) algorithm by applying weighted subsethood based algorithm (WSBA) in FTS algorithm using segmented electricity load demand time series data. …”
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  10. 10
    A Thresholding Algorithm for Text/Background Segmentation in Degraded Handwritten Jawi Documents

    A Thresholding Algorithm for Text/Background Segmentation in Degraded Handwritten Jawi Documents by Tengku Mohd Afendi, Zulcaffle, Othman, A.K., Abidin, W.A.W.Z, Shahrol, Mohamaddan, Ade Syaheda Wani, Marzuki

    Published 2010
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  11. 11
    Development of lung cancer prediction system using meta-heuristic optimized deep learning model

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…After that cancer-affected region in the lung is segmented with the help of the proposed Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. …”
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  12. 12
    Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset

    Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset by Chiang, Yi Fan

    Published 2017
    “…In post-processing, the contour of liver is smooth by binary Gaussian filter. The liver segmentation program with proposed algorithm is evaluated with CT datasets obtained from SLIVER07 to prove its effectiveness in liver segmentation. …”
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  13. 13
    Curvelet based automatic segmentation of supraspinatus tendon from ultrasound image: A focused assistive diagnostic method

    Curvelet based automatic segmentation of supraspinatus tendon from ultrasound image: A focused assistive diagnostic method by Gupta, R., Elamvazuthi, I., Dass, S.C., Faye, I., Vasant, Pa., George, J., Izza, F.

    Published 2014
    “…The segmentation assessment was performed using true positives rate, false positives rate and also accuracy of segmentation. …”
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  14. 14
    Frame removal for mushaf Al-Quran using irregular binary region

    Frame removal for mushaf Al-Quran using irregular binary region by Bany Melhem, Laith Nazeeh, Arbain, Nur Atikah, Azmi, Mohd Sanusi, Muda, Azah Kamilah, A. Jalil, Intan Ermahani, Ramdan, Jabril

    Published 2019
    “…The fault in segmentation process affects the holiness of Al-Quran. …”
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  15. 15
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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  16. 16
    Curvelet based automatic segmentation of supraspinatus tendon from ultrasound image: A focused assistive diagnostic method

    Curvelet based automatic segmentation of supraspinatus tendon from ultrasound image: A focused assistive diagnostic method by Gupta, R., Elamvazuthi, I., Dass, S.C., Faye, I., Vasant, P., George, J., Izza, F.

    Published 2014
    “…The segmentation assessment was performed using true positives rate, false positives rate and also accuracy of segmentation. …”
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  17. 17
    Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD)

    Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD) by Gilani Mohamed, Mohamed Ahmed

    Published 2022
    “…The algorithm will be applied once the ROI has been specified. …”
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  18. 18
    Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification

    Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

    Published 2025
    “…This study investigated the feasibility and effectiveness of image-based techniques using advanced deep learning algorithms to quantify desiccation cracks in expansive soils. …”
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  19. 19
    Illumination removal and text segmnetation for Al-Quran using binary representation

    Illumination removal and text segmnetation for Al-Quran using binary representation by Nazeeh Jamil Bany Melhem

    Published 2015
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  20. 20
    A novel deep learning instance segmentation model for automated marine oil spill detection

    A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

    Published 2020
    “…So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. …”
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