Classification of human carcinoma cells using multispectral imagery
Date
2016
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Proceedings of SPIE Vol. 9791, Medical Imaging 2016: Digital Pathology
Print ISSN
1605-7422
Electronic ISSN
Publisher
SPIE
Volume
9791
Issue
Pages
1 - 6
Language
English
Type
Journal Title
Journal ISSN
Volume Title
Series
Abstract
In this paper, we present a technique for automatically classifying human carcinoma cell images using textural features. An image dataset containing microscopy biopsy images from different patients for 14 distinct cancer cell line type is studied. The images are captured using a RGB camera attached to an inverted microscopy device. Texture based Gabor features are extracted from multispectral input images. SVM classifier is used to generate a descriptive model for the purpose of cell line classification. The experimental results depict satisfactory performance, and the proposed method is versatile for various microscopy magnification options.