Abstract #3829
Accurate Segmentation of Breast Lesions Based on Wavelet Kinetics: Comparison with Semi-Quantitative Features
Saeedeh Navaei Lavasani 1,2 , Masoomeh Gity 3 , Anahita Fathi Kazerooni 1,2 , and Hamidreza Saligheh Rad 1,2
1
Quantitative MR Imaging and Spectroscopy
Group, Research Center for Molecular and Cellular
Imaging, Tehran University of Medical Sciences, Tehran,
Iran,
2
Department of Medical Physics and
Biomedical Engineering, School of Medicine, Tehran
University of Medical Sciences, Tehran, Iran,
3
Department
of Radiology, School of Medicine, Tehran University of
Medical Sciences, Tehran, Iran
Breast cancer is a significant public health problem in
the world. Automatic and objective analysis of DCE-MRI
studies can greatly assist the radiologist to gain
accurate evaluation of tumor size, malignancy and
perfusion in the surrounding tissues, which is essential
in diagnosis. In this work, we proposed breast lesion
segmentation by means of fuzzy c-means clustering
technique using wavelet kinetic and semi-quantitative
features, extracted from the pixel-based time-signal
intensity curves.
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