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

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

^*Bu çalışma için yazışmadan sorumlu yazar

Fatih Sultan Mehmet Vakif Universitesi
Optofil Optik Ve Elektronik Tasarim A.Ş.
Koc University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

Özet

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.

Tercüme edilen katkı başlığı	Experimental Comparison of YOLO-based Models for White Blood Cell Detection
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9798331566555
DOI'lar	https://doi.org/10.1109/SIU66497.2025.11112053
Yayın durumu	Yayınlandı - 2025
Harici olarak yayınlandı	Evet
Etkinlik	33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Istanbul, Turkey Süre: 25 Haz 2025 → 28 Haz 2025

Yayın serisi

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025
Ülke/Bölge	Turkey
Şehir	Istanbul
Periyot	25/06/25 → 28/06/25

Bibliyografik not

Publisher Copyright:
© 2025 IEEE.

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 3 Sağlık ve Kaliteli Yaşam

Keywords

White blood cell classification
White blood cell detection
YOLO-based models

Belgeye Erişim

10.1109/SIU66497.2025.11112053

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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).

@inproceedings{de5923e8b46e477f8b969b0ed532fde7,

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",

address = "United States",

}

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).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

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

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

BM SKH

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap