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Proceedings Paper

Three-dimensional active contour model for characterization of solid breast masses on three-dimensional ultrasound images
Author(s): Berkman Sahiner; Aditya Ramachandran; Heang-Ping Chan; Marilyn A. Roubidoux; Lubomir M. Hadjiiski; Mark A. Helvie; Nicholas Petrick; Chuan Zhou
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Paper Abstract

The accuracy of discrimination between malignant and benign solid breast masses on ultrasound images may be improved by using computer-aided diagnosis and 3-D information. The purpose of this study was to develop automated 3-D segmentation and classification methods for 3-D ultrasound images, and to compare the classification accuracy based on 2-D and 3-D segmentation techniques. The 3-D volumes were recorded by translating the transducer across the lesion in the z-direction while conventional 2-D images were acquired in the x-y plane. 2-D and 3-D segmentation methods based on active contour models were developed to delineate the mass boundaries. Features were automatically extracted based on the segmented mass shapes, and were merged into a malignancy score using a linear classifier. 3-D volumes containing biopsy-proven solid breast masses were collected from 102 patients (44 benign and 58 malignant). A leave-one-out method was used for feature selection and classifier design. The area Az under the test receiver operating characteristic curves for the classifiers using the 3-D and 2-D active contour boundaries were 0.88 and 0.84, respectively. More than 45% of the benign masses could be correctly identified using the 3-D features without missing a malignancy. Our results indicate that an accurate computer classifier can be designed for differentiation of malignant and benign solid breast masses on 3-D sonograms.

Paper Details

Date Published: 15 May 2003
PDF: 9 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.483548
Show Author Affiliations
Berkman Sahiner, Univ. of Michigan (United States)
Aditya Ramachandran, Univ. of Michigan (United States)
Heang-Ping Chan, Univ. of Michigan (United States)
Marilyn A. Roubidoux, Univ. of Michigan (United States)
Lubomir M. Hadjiiski, Univ. of Michigan (United States)
Mark A. Helvie, Univ. of Michigan (United States)
Nicholas Petrick, FDA, Ctr. for Devices and Radiological Health (United States)
Chuan Zhou, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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