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2025, Vol: 11, Issue: 3
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Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making

Omid Eslamifar, Mohammadreza Soltani, Seyed Mohammad Jalal Rastegar Fatemi.


Abstract
Background: Accurate classification of human blood cells is crucial for diagnosing hematological disorders, including infections, inflammation, and leukemia. Manual examination of blood smears is widely used but is time-consuming, subjective, and prone to error. Automated approaches are needed to enhance diagnostic efficiency and reliability.
Methods: This study proposes a hybrid automated classification framework that integrates deep learning with shape transformation techniques. Contourlet transform was employed for shape-based feature extraction, while a recurrent artificial neural network (RANN) was applied for deep feature learning. The African Vulture Optimization Algorithm (AVOA) was employed to optimize feature selection, and a clustering-based decision-making strategy was implemented for the final classification.
Results: The proposed framework demonstrated high classification accuracy across five major blood cell types: lymphocytes (91%), monocytes (97%), eosinophils (94%), basophils (69%), and neutrophils (75%). The integration of contourlet transform and RANN improved feature representation, while AVOA enhanced classification robustness by optimizing feature subsets.
Conclusion: The results indicate that the proposed hybrid model significantly improves diagnostic precision by combining shape-based and deep learning features with advanced optimization techniques. This framework shows potential for clinical translation as a reliable and efficient tool for automated hematology diagnostics.

Key words: White blood cell, classification, contourlet transform, recurrent neural network, precision


 
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How to Cite this Article
Pubmed Style

Eslamifar O, Soltani M, Fatemi SMJR. Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making. Ulutas Med J. 2025; 11(3): 47-61. doi:10.5455/umj.20250424051519

Web Style

Eslamifar O, Soltani M, Fatemi SMJR. Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making. https://www.ulutasmedicaljournal.com/?mno=254245 [Access: October 02, 2025]. doi:10.5455/umj.20250424051519

AMA (American Medical Association) Style

Eslamifar O, Soltani M, Fatemi SMJR. Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making. Ulutas Med J. 2025; 11(3): 47-61. doi:10.5455/umj.20250424051519


Vancouver/ICMJE Style

Eslamifar O, Soltani M, Fatemi SMJR. Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making. Ulutas Med J. (2025), [cited October 02, 2025]; 11(3): 47-61. doi:10.5455/umj.20250424051519


Harvard Style

Eslamifar, O., Soltani, . M. & Fatemi, . S. M. J. R. (2025) Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making. Ulutas Med J, 11 (3), 47-61. doi:10.5455/umj.20250424051519


Turabian Style

Eslamifar, Omid, Mohammadreza Soltani, and Seyed Mohammad Jalal Rastegar Fatemi. 2025. Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making. THE ULUTAS MEDICAL JOURNAL, 11 (3), 47-61. doi:10.5455/umj.20250424051519


Chicago Style

Eslamifar, Omid, Mohammadreza Soltani, and Seyed Mohammad Jalal Rastegar Fatemi. "Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making." THE ULUTAS MEDICAL JOURNAL 11 (2025), 47-61. doi:10.5455/umj.20250424051519


MLA (The Modern Language Association) Style

Eslamifar, Omid, Mohammadreza Soltani, and Seyed Mohammad Jalal Rastegar Fatemi. "Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making." THE ULUTAS MEDICAL JOURNAL 11.3 (2025), 47-61. Print. doi:10.5455/umj.20250424051519


APA (American Psychological Association) Style

Eslamifar, O., Soltani, . M. & Fatemi, . S. M. J. R. (2025) Multiclass Blood Cell Classification Using Contourlet Transform and Metaheuristic-Optimized Deep Features with Clustering-Based Decision Making. THE ULUTAS MEDICAL JOURNAL, 11 (3), 47-61. doi:10.5455/umj.20250424051519


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