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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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