Segmentation of White Blood Cell from Acute Lymphoblastic Leukemia Images Using Dual-Threshold Method.
We propose a dual-threshold method based on a strategic combination of RGB and HSV color space for white blood cell (WBC) segmentation. The proposed method consists of three main parts: preprocessing, threshold segmentation, and postprocessing. In the preprocessing part, we get two images for further processing: one contrast-stretched gray image and one H component image from transformed HSV color space. In the threshold segmentation part, a dual-threshold method is proposed for improving the conventional single-threshold approaches and a golden section search method is used for determining the optimal thresholds. For the postprocessing part, mathematical morphology and median filtering are utilized to denoise and remove incomplete WBCs. The proposed method was tested in segmenting the lymphoblasts on a public Acute Lymphoblastic Leukemia (ALL) image dataset. The results show that the performance of the proposed method is better than single-threshold approach independently performed in RGB and HSV color space and the overall single WBC segmentation accuracy reaches 97.85%, showing a good prospect in subsequent lymphoblast classification and ALL diagnosis.
State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an 710119, China; University of Chinese Academy of Sciences, 52 Sanlihe Road, Beijing 100864, China.
Yan
0000-0002-4171-4590
Y
Li
State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an 710119, China.
Rui
0000-0002-1069-9359
R
Zhu
State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an 710119, China.
Lei
0000-0003-3228-0871
L
Mi
State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an 710119, China; University of Chinese Academy of Sciences, 52 Sanlihe Road, Beijing 100864, China.
Yihui
Y
Cao
Shenzhen Vivolight Medical Device and Technology Co., Ltd., Shenzhen 518000, China.
Di
D
Yao
D000465:Algorithms; D003116:Color; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007958:Leukocyte Count; D007962:Leukocytes / Q000166:cytology*; D008214:Lymphocytes / Q000166:cytology; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000097:blood* / Q000000981:diagnostic imaging*; D012984:Software; D014584:User-Computer Interface