DocumentCode :
3588393
Title :
Comparative study of classification techniques used in skin lesion detection systems
Author :
Jamil, Uzma ; Khalid, Shehzad
Author_Institution :
Dept. of Comput. Eng., Bahria Univ., Islamabad, Pakistan
fYear :
2014
Firstpage :
266
Lastpage :
271
Abstract :
The major branch of data mining used to assign raw data to a particular group is classification. It is a method used to forecast the group association for data objects. Medical Imaging is dealing with the designing of automated systems to help physician diagnosis. In this paper, we present the comprehensive study of some classification techniques used in Medical Imaging. Several types of classification methods including Support Vector Machine, Bayesian networks, Neural networks, k-nearest neighbor classifier, and fuzzy logic techniques are used for this purpose. This study is providing a wide-ranging review of classification techniques used in medical diagnostic systems like diabetic retinopathy, foot ulcer and other related to medical field.
Keywords :
belief networks; data mining; fuzzy logic; image classification; medical image processing; object detection; skin; support vector machines; Bayesian network; classification technique; data mining; fuzzy logic technique; k-nearest neighbor classifier; medical diagnostic system; medical imaging; neural networks; skin lesion detection system; support vector machine; Accuracy; Algorithm design and analysis; Bayes methods; Biomedical imaging; Classification algorithms; Lesions; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multi-Topic Conference (INMIC), 2014 IEEE 17th International
Print_ISBN :
978-1-4799-5754-5
Type :
conf
DOI :
10.1109/INMIC.2014.7097349
Filename :
7097349
Link To Document :
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