Shenzhen Vivolight Medical Device and Technology Co.

Shenzhen, China

Shenzhen Vivolight Medical Device and Technology Co.

Shenzhen, China

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Li Y.,Photonics Optics Tech | Li Y.,University of Chinese Academy of Sciences | Zhu R.,Photonics Optics Tech | Mi L.,Photonics Optics Tech | And 3 more authors.
ICIC Express Letters, Part B: Applications | Year: 2016

In this paper, an improved HSV color space based Acute Lymphoblastic Leukemia (ALL) image segmentation scheme is proposed to improve accuracy of segmentation on digital microscope color images, especially for those taken in non-uniform background illumination conditions and by a microscope with different magnifications. The proposed method has several steps including contrast stretching, color space transformation, threshold segmentation, morphological operations and median filtering. Adopting two thresholds is the innovation of this work. For performance evaluation, 260 ALL blood cell images from ALL IDB2-a public and free available blood sample dataset are used. The experimental results show the proposed method gets a higher accuracy in segmenting both high- and low- contrast blood cell images than the original HSV color space based single threshold method, showing a better prospect in subsequent automatic acute lymphoblastic leukemia feature extraction and classification. © 2016 ICIC International.


Li Y.,CAS Xi'an Institute of Optics and Precision Mechanic | Li Y.,University of Chinese Academy of Sciences | Zhu R.,CAS Xi'an Institute of Optics and Precision Mechanic | Mi L.,CAS Xi'an Institute of Optics and Precision Mechanic | And 3 more authors.
Computational and Mathematical Methods in Medicine | Year: 2016

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. © 2016 Yan Li et al.


PubMed | Shenzhen Vivolight Medical Device and Technology Co. and CAS Xi'an Institute of Optics and Precision Mechanic
Type: | Journal: Computational and mathematical methods in medicine | Year: 2016

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.

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