Automatic classification of cells using morphological shape in peripheral blood images

KyungSu Kim; Jeongjun Song; Forouzan Golshani; Sethuraman Panchanathan

doi:10.1117/12.403813

11 October 2000 Automatic classification of cells using morphological shape in peripheral blood images

KyungSu Kim, Jeongjun Song, Forouzan Golshani, Sethuraman Panchanathan

Proceedings Volume 4210, Internet Multimedia Management Systems; (2000) https://doi.org/10.1117/12.403813
Event: Information Technologies 2000, 2000, Boston, MA, United States

Abstract

A novel technique for automatic analysis and classification of cells in peripheral blood images is presented. The purposes of this research are to analyze and classify morphological shapes of mature red-blood cells and white-blood cells in peripheral blood images. We first, identify red-blood cells and white-blood cells in a blood image captured from CCD camera attached to microscope. Feature extraction is the second step. Finally blood cells are classified using back propagation neural network. Fifteen different classification clusters including normal cells are in red blood cell. However, there are five different normal categories in discrimination of white blood cells. In other words, the system can tell whether a I've white cell belongs to one of the five normal classes or not. A novel segmentation method is presented for extraction of nucleus and cytoplasm which inherently posses valuable clues in white blood cell classification. Initially, seventy-six dimensions of a feature vector that includes UNL Fourier descriptor shape, and color are considered in red-blood cell classification. While 38 dimensions of a feature vector are considered in red blood cell classification. Based on the proposed method, a prototype system has implemented and evaluated with various classification algorithms such as LVQ-3 (Learning Vector Quantization) and K-NN (K- nearest neighbor). The experiment results show that the proposed method out performs on blood cell classification compared with other alternatives.

Citation Download Citation

KyungSu Kim, Jeongjun Song, Forouzan Golshani, and Sethuraman Panchanathan "Automatic classification of cells using morphological shape in peripheral blood images", Proc. SPIE 4210, Internet Multimedia Management Systems, (11 October 2000); https://doi.org/10.1117/12.403813

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available