Deteksi Limfoblas pada Citra Sel Darah Menggunakan Fitur Geometri dan Local Binary Pattern

Annisaa Sri Indrawanti, Eka Prakarsa Mandyartha


Lymphoblasts are white blood cell types of lymphocytes, which can mark leukemia. To identify lymphoblasts, an analysis of white blood cells is required. In this study, a computer-based automated system was proposed using digital image processing techniques to detect lymphoblasts by analyzing microscopic images of blood cells. This proposed method segments the components of white blood cells, which are cytoplasm and nucleus, using a new approach based on adaptive local thresholding techniques. After each cell component was segmented, the geometry features and texture were extracted. The texture feature used a local binary pattern (LBP) descriptor from the nucleus. The set of features was used to train the support vector machine classification algorithm in detecting lymphoblasts. The proposed method is able to segment correctly 264 of 269 total white blood cells, with 98.14% accuracy, out of 35 acute lymphoblastic leukemia images taken with the same camera with the same lighting conditions. The use of geometry features with 16 dimensional feature vector and LBP features with 256 dimensional feature vector result in accuracy of lymphoblast identification of 88.79% and 89.72% respectively. Better performance is obtained by combining two features, the geometry and the LBP with 272 dimensional feature vector, with classification accuracy of 94.32%.


deteksi sel limfoblas, fitur geometri, fitur tekstur local binary pattern, pengolahan citra.

Full Text:



N. Isnani, D.A. Perwitasari, R. Andalusia, dan H.I. Mahdi, "Evaluasi Toksisitas Hematologi Akibat Penggunaan 6-Merkaptopurin dalam Fase Pemeliharaan pada Pasien Pediatri Kanker Leukimia Limfoblastik Akut di RS Kanker Dharmais Jakarta," Media Farmasi, Vol.11, No.1, hal. 90-97, 2014.

V.N. Tran, W. Ismail, R. Hassan, dan A. Yoshitaka, "An Automated Method for the Nuclei and Cytoplasm of Acute Myeloid Leukemia Detection in Blood Smear Images," World Automation Congress (WAC) IEEE, 2016, hal. 1-6.

L. Faivdullah, F. Azahar, Z.Z. Htike, dan W.N. Naing, "Leukemia Detection from Blood Smears," Journal of Medical and Bioengineering, Vol. 4, No. 6, hal. 488–491, 2015.

S. Mohapatra, D. Patra, dan S. Satpathy, "Automated Morphometric Classification of Acute Lymphoblastic Leukaemia in Blood Microscopic Images Using an Ensemble of Classifiers," Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Vol. 4, No. 1, hal. 3–16, 2016.

E.P. Mandyartha dan C. Fatichah, "Three-level Local Thresholding Berbasis Metode Otsu untuk Segmentasi Leukosit pada Citra Leukemia Limfoblastik Akut," Jurnal Buana Informatika, Vol. 7, No. 1, hal. 43-54, 2016.

R.D. Labati, V. Piuri, dan F. Scotti, "All-IDB: The Acute Lymphoblastic Leukemia Image Database for Image Processing," Proc. of the 18th IEEE ICIP International Conference on Image Processing, 2011, hal. 2045-2048.

V. Singhal dan P. Singh, "Texture Features for the Detection of Acute Lymphoblastic Leukemia," Proc. of International Conference on ICT for Sustainable Development, 2016, hal. 535-543.

M.M. Amin, S. Kermani, A. Talebi, dan M.G. Oghli, "Recognition of Acute Lymphoblastic Leukemia Cells in Microscopic Image Using KMeans Clustering and Support Vector Machine Classifier," Journal of Medical Signals and Sensors, Vol. 5, No.1, hal. 49-50, 2015.

S. Mishra, B. Majhi, P.K. Sa, dan L. Sharma, "Gray Level Co-Occurrence Matrix and Random Forest Based Acute Lymphoblastic Leukemia Detection," Biomedical Signal Processing and Control, Vol. 33, hal. 272-280, 2017.

D.R. Karthikeyan dan N. Poornima, “Microscopic Image Segmentation Using Fuzzy C Means for Leukemia Diagnosis,” International Journal of Advanced Research in Science, Engineering and Technology, Vol. 4, No. 1, hal. 3136-3142, 2017.

T. Nguyen and S. Nahavandi, "Modified AHP for Gene Selection and Cancer Classification Using Type-2 Fuzzy Logic," IEEE Transactions on Fuzzy Systems, Vol. 24, No. 2, hal. 273-287, 2016.

V. Singhal dan P. Singh, "Local Binary Pattern for Automatic Detection of Acute Lymphoblastic Leukemia," Proc. of 2014 Twentieth National Conference on Communications (NCC), 2014, hal. 1–5.



  • There are currently no refbacks.

Copyright (c) 2018 Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI)

JNTETI (Jurnal Nasional Teknik Elektro dan Teknologi Informasi)

Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik Universitas Gadjah Mada
Jl. Grafika No 2. Kampus UGM Yogyakarta 55281
+62 274 552305