التفاصيل البيبلوغرافية
| العنوان: |
Medical X-Ray Image Clustering Using a New Gabor Function-Based Image Representation. |
| المؤلفون: |
Fesharaki, Nooshin Jafari, Pourghassem, Hossein |
| المصدر: |
International Review on Computers & Software; May2012, Vol. 7 Issue 3, p1100-1106, 7p |
| مصطلحات موضوعية: |
X-ray imaging, DIAGNOSTIC imaging, IMAGE representation, NUMBER theory, SUPPORT vector machines, FEATURE extraction, PERFORMANCE evaluation |
| مستخلص: |
Nowadays, by generating a numerous number of medical images as well as their wide-spread usage in many different medicine applications, the need for more powerful searching and retrieving engines is ever-increasing. As a result, clustering plays meanwhile an important role in organizing medical images. In this paper, we try to develop a new image clustering framework by using Gabor function based on image representation which reduces the complexities in extracting the utilized features. The features in global and pixel levels are then extracted from these new image representations. Finally, a one-against-one multi-class Support Vector Machine (SVM) classifier is applied to cluster medical images. In this task, a dataset consisting of different medical X-ray images is used to evaluate the proposed clustering scheme and its effectiveness is shown according to the presented experimental results. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
