Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Classification of Human Carcinoma Cells Using Multispectral Imagery
Download
index.pdf
Date
2016-03-03
Author
Çinar, Umut
Çetin, Yasemin
Atalay, Rengül
Cetin, Enis
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
3
views
2
downloads
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.
Subject Keywords
Multispectral imaging
,
Automatic classification
,
Cancer cells
,
Gabor features
,
Microscopy
URI
https://hdl.handle.net/11511/57776
DOI
https://doi.org/10.1117/12.2217022
Collections
Graduate School of Informatics, Conference / Seminar