Abstract #2300
Accurate Classification of Parotid Tumors Based on Histogram Analysis of ADC-maps
Sanam Assili 1,2 , Anahita Fathi Kazerooni 1,3 , Mahnaz Nabil 1,4 , Leila Agha Ghazvini 5 , Mojtaba Safari 1 , and Hamidreza Saligheh Rad 1
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, School of Medicine, Tabriz
University of Medical Sciences, Tabriz, Iran,
3
Department
of Medical Physics and Biomedical Engineering, School of
Medicine, Tehran University of Medical Sciences, Tehran,
Iran,
4
Department
of Statistics, Tarbiat Modares University, Tehran, Iran,
5
Department
of Radiology, School of Medicine, Tehran University of
Medical Sciences, Tehran, Iran
Accurate discrimination of benign and malignant parotid
tumors in morphological MR images is a challenging
issue. On one hand there exist large histological
variations throughout the tumor, and on the other hand
anatomical MR-derived features have low sensitivity in
capturing the physiological non-uniformities of parotid
tumors. To overcome this problem, in this work, we have
explored and compared several quantitative measures
extracted from ADC map to find the best parameters in
distinguishing benign and malignant parotid tumors, in
an automatic classification scheme.
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