Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi

Atif Eren Yarikan; Irem Eylul Oztek; Zeki Kus; Berna Kiraz; Alper Kiraz

doi:10.1109/SIU66497.2025.11112053

Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi

Translated title of the contribution: Experimental Comparison of YOLO-based Models for White Blood Cell Detection

Atif Eren Yarikan^*, Irem Eylul Oztek, Zeki Kus, Berna Kiraz, Alper Kiraz

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The detection, classification, and analysis of white blood cells, which are one of the fundamental components of the immune system, are of great importance for the diagnosis of diseases such as infections and cancer. Therefore, automated analysis methods that can quickly and accurately identify and classify white blood cells in peripheral blood smear images are highly significant. In this study, four different YOLO-based models were used for the detection and classification of white blood cells, and their performances were comparatively evaluated. For the experimental studies, the LeukemiaAttri dataset, designed for leukemia diagnosis, was utilized. The results demonstrated that the YOLOv9t and YOLOv11n models outperformed the other models. Additionally, the class-based performance of the YOLOv9t model was examined. These findings indicate that YOLO-based methods are effective for the detection and classification of white blood cells.

Translated title of the contribution	Experimental Comparison of YOLO-based Models for White Blood Cell Detection
Original language	Turkish
Title of host publication	33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331566555
DOIs	https://doi.org/10.1109/SIU66497.2025.11112053
Publication status	Published - 2025
Externally published	Yes
Event	33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Istanbul, Turkey Duration: 25 Jun 2025 → 28 Jun 2025

Publication series

Name	33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings

Conference

Conference	33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025
Country/Territory	Turkey
City	Istanbul
Period	25/06/25 → 28/06/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/SIU66497.2025.11112053

Cite this

Yarikan, A. E., Eylul Oztek, I., Kus, Z., Kiraz, B., & Kiraz, A. (2025). Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi. In 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings (33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU66497.2025.11112053

Yarikan, Atif Eren ; Eylul Oztek, Irem ; Kus, Zeki et al. / Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi. 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2025. (33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings).

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title = "Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi",

abstract = "The detection, classification, and analysis of white blood cells, which are one of the fundamental components of the immune system, are of great importance for the diagnosis of diseases such as infections and cancer. Therefore, automated analysis methods that can quickly and accurately identify and classify white blood cells in peripheral blood smear images are highly significant. In this study, four different YOLO-based models were used for the detection and classification of white blood cells, and their performances were comparatively evaluated. For the experimental studies, the LeukemiaAttri dataset, designed for leukemia diagnosis, was utilized. The results demonstrated that the YOLOv9t and YOLOv11n models outperformed the other models. Additionally, the class-based performance of the YOLOv9t model was examined. These findings indicate that YOLO-based methods are effective for the detection and classification of white blood cells.",

keywords = "White blood cell classification, White blood cell detection, YOLO-based models",

author = "Yarikan, \{Atif Eren\} and \{Eylul Oztek\}, Irem and Zeki Kus and Berna Kiraz and Alper Kiraz",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 ; Conference date: 25-06-2025 Through 28-06-2025",

year = "2025",

doi = "10.1109/SIU66497.2025.11112053",

language = "T{\"u}rk{\c c}e",

series = "33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings",

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Yarikan, AE, Eylul Oztek, I, Kus, Z, Kiraz, B & Kiraz, A 2025, Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi. in 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings. 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025, Istanbul, Turkey, 25/06/25. https://doi.org/10.1109/SIU66497.2025.11112053

Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi. / Yarikan, Atif Eren; Eylul Oztek, Irem; Kus, Zeki et al.
33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2025. (33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi

AU - Yarikan, Atif Eren

AU - Eylul Oztek, Irem

AU - Kus, Zeki

AU - Kiraz, Berna

AU - Kiraz, Alper

PY - 2025

Y1 - 2025

N2 - The detection, classification, and analysis of white blood cells, which are one of the fundamental components of the immune system, are of great importance for the diagnosis of diseases such as infections and cancer. Therefore, automated analysis methods that can quickly and accurately identify and classify white blood cells in peripheral blood smear images are highly significant. In this study, four different YOLO-based models were used for the detection and classification of white blood cells, and their performances were comparatively evaluated. For the experimental studies, the LeukemiaAttri dataset, designed for leukemia diagnosis, was utilized. The results demonstrated that the YOLOv9t and YOLOv11n models outperformed the other models. Additionally, the class-based performance of the YOLOv9t model was examined. These findings indicate that YOLO-based methods are effective for the detection and classification of white blood cells.

AB - The detection, classification, and analysis of white blood cells, which are one of the fundamental components of the immune system, are of great importance for the diagnosis of diseases such as infections and cancer. Therefore, automated analysis methods that can quickly and accurately identify and classify white blood cells in peripheral blood smear images are highly significant. In this study, four different YOLO-based models were used for the detection and classification of white blood cells, and their performances were comparatively evaluated. For the experimental studies, the LeukemiaAttri dataset, designed for leukemia diagnosis, was utilized. The results demonstrated that the YOLOv9t and YOLOv11n models outperformed the other models. Additionally, the class-based performance of the YOLOv9t model was examined. These findings indicate that YOLO-based methods are effective for the detection and classification of white blood cells.

KW - White blood cell classification

KW - White blood cell detection

KW - YOLO-based models

UR - https://www.scopus.com/pages/publications/105015567639

U2 - 10.1109/SIU66497.2025.11112053

DO - 10.1109/SIU66497.2025.11112053

M3 - Konferans katkısı

AN - SCOPUS:105015567639

T3 - 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings

BT - 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025

Y2 - 25 June 2025 through 28 June 2025

ER -

Yarikan AE, Eylul Oztek I, Kus Z, Kiraz B, Kiraz A. Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi. In 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2025. (33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings). doi: 10.1109/SIU66497.2025.11112053

Beyaz Kan H cresi Tespitinde YOLO Tabanli Modellerin Deneysel Kar sila stirmasi

Abstract

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Bibliographical note

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