Title

SMO-based system for identifying common lung conditions using histogram

College

College of Computer Studies

Department/Unit

Computer Technology

Document Type

Conference Proceeding

Source Title

International Symposium on Medical Information and Communication Technology, ISMICT

First Page

112

Last Page

116

Publication Date

8-15-2013

Abstract

A radiograph is a visualization aid that physicians use in identifying lung abnormalities. Although digitized x-ray images are available, diagnosis by a medical expert through pattern recognition is done manually. Thus, this paper presents a system that utilizes machine learning for pattern recognition and classification of three lung conditions, namely Normal, Pleural Effusion and Pneumothorax cases. Using two histogram equalization techniques, the designed system achieves an accuracy rate of 76.19% and 78.10% by using Sequential Minimal Optimization (SMO). © 2013 IEEE.

html

Digitial Object Identifier (DOI)

10.1109/ISMICT.2013.6521711

Disciplines

Computer Sciences

Keywords

Pattern recognition systems; Lungs—Diseases—Imaging; Support vector machines

Upload File

wf_yes

This document is currently not available here.

Share

COinS