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24.Cnf-193 Paper View Page |
| Title |
Mammography mass detection: visual versus statistical features selection |
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| Authors |
Mr. Ibrahim M. Ibrahim, Cairo University, Cairo, Egypt
Dr. Manal Abdel-Wahed, Cairo University, Cairo, Egypt
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| Abstract |
Physician experience of detecting breast cancer can be assisted by using some computerized feature extraction algorithms. The key point is to use the most significant features with the most suitable classifiers. In this study, we introduce a comparative study between two features selection methods like the t-test and the Kull-Leibler divergence and between a, somehow, new selection method done visually by displaying the features through a color heat map. The visual method showed moderate results, but it needs more considerations at applying it. Experimental results are provided to support this claim. |
| Track |
BME: Biomedical Engineering |
| Conference |
1st Mosharaka International Conference on Biomedical Engineering, Electronics and Nanotechnology (MIC-BEN 2011) |
| Congress |
2011 Global Congress on Biomedical Engineering, Electronics and Nanotechnology (GC-BEN 2011), 9-11 September 2011, Amman, Jordan |
| Pages |
37-42 |
| Topics |
Digital Image Processing
Biomedical Imaging Systems
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| ISSN |
2227-331X |
| DOI |
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| BibTeX |
@inproceedings{193BEN2011,
title={Mammography mass detection: visual versus statistical features selection},
author={Ibrahim M. Ibrahim, and Manal Abdel-Wahed},
booktitle={2011 Global Congress on Biomedical Engineering, Electronics and Nanotechnology (GC-BEN 2011)},
year={2011},
pages={37-42},
doi={}},
organization={Mosharaka for Research and Studies}
}
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| Paper Views |
125 |
Paper Views Rank |
45/524 |
| Paper Downloads |
41 |
Paper Downloads Rank |
280/524 |
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