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  1. 1
    MRI brain tumor detection methods using contourlet transform based on time adaptive self-organizing map

    MRI brain tumor detection methods using contourlet transform based on time adaptive self-organizing map by Ali Farzamnia, Seyed Hamidreza Hazaveh, Seyede Safieh Siadat, Ervin Gubin Moung

    Published 2023
    “…In this article, we propose a novel method that uses contourlet transform and time adaptive self-organizing map, optimized by the whale optimization algorithm, in order to distinguish between benign and malignant brain tumors in MRI images. …”
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  2. 2
    Plant leaf recognition algorithm using ant colony-based feature extraction technique

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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  3. 3
    Breast cancer histological images nuclei segmentation and optimized classification with deep learning

    Breast cancer histological images nuclei segmentation and optimized classification with deep learning by Abbasi, Muhammad Inam, Khan, Fawad Salam, Khurram, Muhammad, Mohd, Mohd Norzali, Khan, Muhammad Danial

    Published 2022
    “…A breast cancer multi-classification technique based on a suggested deep learning algorithm was examined to achieve the accuracy of 99.2% using a huge database of ICIAR 2018, demonstrating the method’s efficacy in offering an important weapon for breast cancer multi-classification in a medical setting. …”
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  4. 4
    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules

    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

    Published 2023
    “…Experiments also compare the size of the image as input, using relu activation and adam optimization. …”
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  5. 5
    DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma

    DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…In addition, we combined a RP technique with a support vector machine (SVM) that employs a sequential minimal optimization training algorithm (SMO) in order to efficiently differentiate squamous-cell carcinoma and oral dysplasia. …”
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  6. 6
    An Investigation of Image and Video Classification Algorithm for White Blood Cells Detection in Real Time View

    An Investigation of Image and Video Classification Algorithm for White Blood Cells Detection in Real Time View by Abu Kasim, Nabeela

    Published 2015
    “…The new approach used in separating it by using image classification algorithm to separate the white blood cells from the blood capillaries and it will be done live from a video. …”
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  7. 7
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…A working classification algorithm is developed by using MATLAB and the Fuzzy Logic Toolbox to differentiate and classify the staining pattern of HEp-2 cell images. …”
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  8. 8
    FLUORESCENCE INTENSITY POSITIVITY CLASSIFICATION OF HEP-2 CELLS IMAGES USING FUZZY LOGIC

    FLUORESCENCE INTENSITY POSITIVITY CLASSIFICATION OF HEP-2 CELLS IMAGES USING FUZZY LOGIC by ABANG SAZALI, DAYANG FARZANAI

    Published 2013
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  9. 9
    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic

    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic by Jamil, N.F.B., Faye, I., May, Z.

    Published 2014
    “…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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  10. 10
    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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  11. 11
    Classification red blood cells using support vector machine

    Classification red blood cells using support vector machine by Akrimi J.A., Suliman A., George L.E., Ahmad A.R.

    Published 2023
    “…Cells; Classification (of information); Cytology; Diagnosis; Feature extraction; Image processing; Image segmentation; Imaging techniques; Medical imaging; Support vector machines; Classifier algorithms; Clinical diagnosis; Confusion matrices; Image processing technique; Mean Filte; Red blood cell; Retrieval systems; SVM; Blood…”
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  12. 12
    An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving

    An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving by Jing, Rui Tang, Mat Isa, Nor Ashidi

    Published 2014
    “…In addition, the experiments using cervical cell images and HEp-2 cell images showed great potential of the AFCEDP technique as a technique for enhancing medical microscopic images.…”
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  13. 13
    Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms

    Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms by Wan Azani Mustafa, Khalis Khiruddin, Khairur Rijal Jamaludin, Firdaus Yuslan Khusairi, Shahrina Ismail

    Published 2026
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  14. 14
    Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images

    Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images by Baharom, Mohamad Shahrul Affendi

    Published 2019
    “…However, some of the image suffers from texture’s cell loss. On the other hand, the proposed segmentation method capable to segment cell and isolate most of the combined cell. …”
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  15. 15
    Classification Of Cervical Cancer Stage From Pap Smear Tests

    Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

    Published 2019
    “…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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  16. 16
    Red blood cells classification with sharpening segmentation and mask R-CNN

    Red blood cells classification with sharpening segmentation and mask R-CNN by Arianti, Nunik Destria, Muda, Azah Kamilah, Ahmad, Norashikin

    Published 2023
    “…This paper proposes classification using sharpening segmentation combined with the algorithm mask R-CNN to increase the accuracy of calculating the number of RBCs. …”
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  17. 17
    Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab

    Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab by Wahhab, Hayan Tareq Abdul

    Published 2015
    “…Tettamanti Research Center for childhood leukemia and hematological diseases, Italy. The image segmentation addressed several key issues in blast cells segmentation including, the blast cell localization, sub-imaging, color variation and segregation of touching cells. …”
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  18. 18
    An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing

    An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing by Hajyyev, Abdyrahym

    Published 2014
    “…The algorithm tested on the publicly available Mivia Hep-2 Cell image dataset. …”
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  19. 19
    Lung cancer medical images classification using hybrid CNN-SVM

    Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Vanessa, Penshie, Hamada Rasheed Hassan, Al-Absi

    Published 2021
    “…This algorithm is capable of automatically classifying and analyzing each lung image to check if there is any presence of cancer cells or not. …”
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  20. 20
    Geometric Feature Extraction for Identification and Classification of the Overlapping Cells for Leukaemia

    Geometric Feature Extraction for Identification and Classification of the Overlapping Cells for Leukaemia by Kiu, Siew Ming

    Published 2018
    “…Overlapping cell identification and classification of microscopic blood cell image is proposed to increase the accuracy of the number of automated counting and the percentage of the overall accuracy. …”
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