DocumentCode :
256018
Title :
Comparative analysis of segmentation algorithms for leukocyte extraction in the acute Lymphoblastic Leukemia images
Author :
Rawat, J. ; Singh, A. ; Bhadauria, H.S. ; Kumar, I.
Author_Institution :
CSE Dept., G.B.P.E.C., Pauri, India
fYear :
2014
fDate :
11-13 Dec. 2014
Firstpage :
245
Lastpage :
250
Abstract :
By concerning with the health of the patients, analysis of blood cell particularly morphological structure of leukocyte in microscopic blood smear can effectively detect the important blood disorder such as the Acute Lymphoblastic Leukemia. Unfortunately, the analysis made by hematology expert is not always accurate and rapid due to the error prone modality and operator´s incapability´s. The presented paper shows the how to enhance the microscopic blood smear by removing the unwanted microscopic background by segmenting the cell and analyzing the existing algorithms for segmentation by performing comparative study for effectively segments and accurately measure the leukocyte characteristics in order to allow, subsequent automatic diagnosis of leukemia and other hematic diseases.
Keywords :
blood; diseases; feature extraction; image segmentation; medical image processing; acute lymphoblastic leukemia image; blood cell; blood disorder; error prone modality; hematic disease; hematology; leukocyte extraction; microscopic blood smear; morphological structure; segmentation algorithm; Biomedical imaging; Blood; Image color analysis; Image edge detection; Image segmentation; Microscopy; Vectors; Blood Analysis; Color L∗a∗b space; Global Thresholding; HSV color space; K-means Clustering; Leukocyte segmentation; Marker Controlled Watershed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel, Distributed and Grid Computing (PDGC), 2014 International Conference on
Conference_Location :
Solan
Print_ISBN :
978-1-4799-7682-9
Type :
conf
DOI :
10.1109/PDGC.2014.7030750
Filename :
7030750
Link To Document :
بازگشت