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Microscopic image segmentation based on pixel classification and dimensionality reduction
Author(s) -
Benazzouz Mourtada,
Baghli Ismahan,
Chikh Med Amine
Publication year - 2013
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.22032
Subject(s) - artificial intelligence , segmentation , pattern recognition (psychology) , computer science , pixel , dimensionality reduction , image segmentation , scale space segmentation , computer vision , connected component labeling
Pathological image analysis plays a significant role in effective disease diagnostics. In this article, a tool for diagnosis assistance by automatic segmentation of bone marrow images is introduced. The aim of our segmentation is to demarcate cell's component: nucleus, cytoplasm, red cells, and background. Different color spaces were used to extract color's features to profit of their complementarity. We introduce several dimensionality reduction techniques. These techniques are exemplified on a support vector machine pixel‐based bone marrow image segmentation problem in which it is shown that it may give significant improvement in segmentation accuracy and time consuming. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 22–28, 2013