DocumentCode
2180007
Title
Improving the Discrimination of Benign and Malignant Breast MRI Lesions Using the Apparent Diffusion Coefficient
Author
McClymont, Darryl ; Mehnert, Andrew ; Trakic, Adnan ; Crozier, Stuart ; Kennedy, Dominic
Author_Institution
Sch. of lTEE, Univ. of Queensland, Brisbane, QLD, Australia
fYear
2010
fDate
1-3 Dec. 2010
Firstpage
569
Lastpage
574
Abstract
This paper presents an investigation of the apparent diffusion coefficient (ADC) for improving the discrimination of benign and malignant lesions in breast magnetic resonance imaging (MRI). In particular a method is presented for automatically selecting hyper intense tumour voxels in dynamic contrast enhanced (DCE) MRI data and evaluating their average ADC in the corresponding diffusion-weighted (DW) MRI data. The method was applied to ten breast MRI datasets obtained from routine clinical practice. The results demonstrate that the combination of the relative signal increase (DCE-MRI) with the apparent diffusion coefficient (DW-MRI) leads to better discrimination than with either feature alone. The results also suggest that it is important to acquire the DW-MRI data in a consistent fashion, i.e. either before or after the acquisition of the DCE-MRI data.
Keywords
magnetic resonance imaging; medical image processing; apparent diffusion coefficient; benign breast MRI lesions; diffusion weighted MRI data; dynamic contrast enhanced MRI data; hyper intense tumour voxels; magnetic resonance imaging; malignant breast MRI lesions; MRI; apparent diffusion coefficient; breast cancer; contrast enhancement;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Image Computing: Techniques and Applications (DICTA), 2010 International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-1-4244-8816-2
Electronic_ISBN
978-0-7695-4271-3
Type
conf
DOI
10.1109/DICTA.2010.101
Filename
5692622
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