Segmentation of Acute Lymphoblastic Leukemia Using C-Y Color Space

Abstract

Abstract-Medical image analysis process usually starts with segmentation step, which aims to separate different objects in the image scene. This is achieved by mainly dividing the image into two parts, the region of interest (ROI) and the background. Segmentation of acute lymphoblastic leukemia blood cell (ALL) based on microscope color image is one of the important step in the recognition process. This paper proposed a technique which aims to segment the color image of acute leukemia by transforming the RGB color space to C-Y color space .in the C-Y color space, the luminance component is used to segment (ALL) .The proposed algorithm runs on 100 microscopic ALL images and the experimental result shows that the proposed system can provide a good segmentation of ALL from its complicated background and shows that the segmentation accuracy of the proposed technique is 98.38% compared to the result of the manual segmentation method by expert.

Image Processing Techniques for Acute Leukaemia Detection

“…Images have to be pre-processed before feeding them into the detection system because it greatly impacts segmentation and feature extraction steps. In pre-processing [19] converts RGB image into a grayscale image, but most of the researchers propose that converting RGB model to other colour space like YCBR [6], CY [4], CMYK [17] is more effective. [14] proves that selecting only a green component from an RGB image can also result in better accuracy in segmentation.…”

Detection of Acute Myeloid Leukemia based on White Blood Cell Morphological Imaging using Naïve Bayesian Algorithm

“…Segmentation of the cell nucleus can be performed through the use of the C-Y color space [10]. The C-Y color space serves to transform an RGB image of WBCs into a YCbCr image.…”

“…The proposed study involves the utilization of the C-Y color space to achieve the conversion of an RGB image into a YCbCr image [12] [13]. Segmentation of the nucleus and *Corresponding Author www.ijacsa.thesai.org WBCs is accomplished through the use of the thresholding method followed by median filtering to make the nucleus and WBC [10]. Methods to classify cell and AML types were based on naïve Bayes' classifier algorithm.…”