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Automatic segmentat...
Automatic segmentation of enhancing breast tissue in dynamic contrast-enhanced MR images
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Gal, Yaniv (author)
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- Mehnert, Andrew, 1967 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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Bradley, Andrew (author)
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McMahon, Kerry (author)
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Crozier, Stuart (author)
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(creator_code:org_t)
- ISBN 0769530672
- 2007
- 2007
- English.
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In: Proc. 2007 Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA). - 0769530672 ; , s. 124-129
- Related links:
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https://research.cha...
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https://doi.org/10.1...
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Abstract
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- We present a novel method for the segmentation of enhancing breast tissue, suspicious of malignancy, in dynamic contrast-enhanced (DCE) MR images. The method is based on seeded region growing and merging using criteria based on both the original image intensity values and the fitted parameters of a novel empiric parametric model of contrast enhancement. We present the results of the application of the method to DCE-MRI data sets originating from breast MRI examinations of 24 subjects (10 cases of benign and 14 cases of malignant enhancement). The results show that the segmentation method has 100% sensitivity for the detection of suspicious regions independently identified by a radiologist. The results suggest that the method has potential both as a tool to assist the clinician with the task of locating suspicious tissue and as input to a computer assisted diagnostic system for generating quantitative features for automatic classification of suspicious tissue.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
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