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.

Highlights

  • Cancer is a class of diseases characterized by out-ofcontrol cell growth

  • In [9] proposed algorithm Based on HSI color space, enhancement technique .In this paper we proposed a segmentation algorithm on digital microscope images for acute lymphoblastic leukemia based on C-Y color space

  • In this presented work we introduced an approach of segmentation the acute leukemia blood cell (ALL) based on C-Y color space

Read more

Summary

Introduction

Cancer is a class of diseases characterized by out-ofcontrol cell growth. There are many different types of cancer, and each is classified by the type of cell that is initially affected, one of them is Leukemia. Leukemia is a cancer that begins in the bone marrow. It is caused by excessive production of leucocytes that replace normal blood cells. There are four major different types of Leukemia according to the growth speed overproduction of leukemic cells [1]. The four main types of Leukemia are : Acute lymphoblastic leukemia (ALL)

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call