Automatic boundary extraction of ultrasonic breast lesions

Anant Madabhushi; Dimitris Metaxas

doi:10.1109/ISBI.2002.1029329

Automatic boundary extraction of ultrasonic breast lesions

Anant Madabhushi, Dimitris Metaxas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

20 Scopus citations

Abstract

Breast cancer is the second leading cause of mortality in women. Automatically detecting tumors and extracting lesion boundaries in sonograms is difficult due to the specular and noisy nature of these images. Algorithms that claim to automatically classify ultrasonic breast lesions, rely on manual delineation of the tumor boundaries. This is however a slow and cumbersome task. In this work, we combine texture, intensity, gradient and a deformable model along with empirically determined domain specific knowledge to automatically find lesion margins in ultrasound images with no human intervention. The system has successfully extracted tumor boundaries in over 30 breast sonograms.

Original language	English (US)
Title of host publication	2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
Publisher	IEEE Computer Society
Pages	601-604
Number of pages	4
ISBN (Electronic)	078037584X
DOIs	https://doi.org/10.1109/ISBI.2002.1029329
State	Published - 2002
Externally published	Yes
Event	IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States Duration: Jul 7 2002 → Jul 10 2002

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2002-January
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Other

Other	IEEE International Symposium on Biomedical Imaging, ISBI 2002
Country/Territory	United States
City	Washington
Period	7/7/02 → 7/10/02

All Science Journal Classification (ASJC) codes

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI.2002.1029329

Cite this

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title = "Automatic boundary extraction of ultrasonic breast lesions",

abstract = "Breast cancer is the second leading cause of mortality in women. Automatically detecting tumors and extracting lesion boundaries in sonograms is difficult due to the specular and noisy nature of these images. Algorithms that claim to automatically classify ultrasonic breast lesions, rely on manual delineation of the tumor boundaries. This is however a slow and cumbersome task. In this work, we combine texture, intensity, gradient and a deformable model along with empirically determined domain specific knowledge to automatically find lesion margins in ultrasound images with no human intervention. The system has successfully extracted tumor boundaries in over 30 breast sonograms.",

author = "Anant Madabhushi and Dimitris Metaxas",

note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; IEEE International Symposium on Biomedical Imaging, ISBI 2002 ; Conference date: 07-07-2002 Through 10-07-2002",

year = "2002",

doi = "10.1109/ISBI.2002.1029329",

language = "English (US)",

series = "Proceedings - International Symposium on Biomedical Imaging",

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pages = "601--604",

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Madabhushi, A & Metaxas, D 2002, Automatic boundary extraction of ultrasonic breast lesions. in 2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings., 1029329, Proceedings - International Symposium on Biomedical Imaging, vol. 2002-January, IEEE Computer Society, pp. 601-604, IEEE International Symposium on Biomedical Imaging, ISBI 2002, Washington, United States, 7/7/02. https://doi.org/10.1109/ISBI.2002.1029329

Automatic boundary extraction of ultrasonic breast lesions. / Madabhushi, Anant; Metaxas, Dimitris.
2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings. IEEE Computer Society, 2002. p. 601-604 1029329 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2002-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Breast cancer is the second leading cause of mortality in women. Automatically detecting tumors and extracting lesion boundaries in sonograms is difficult due to the specular and noisy nature of these images. Algorithms that claim to automatically classify ultrasonic breast lesions, rely on manual delineation of the tumor boundaries. This is however a slow and cumbersome task. In this work, we combine texture, intensity, gradient and a deformable model along with empirically determined domain specific knowledge to automatically find lesion margins in ultrasound images with no human intervention. The system has successfully extracted tumor boundaries in over 30 breast sonograms.

AB - Breast cancer is the second leading cause of mortality in women. Automatically detecting tumors and extracting lesion boundaries in sonograms is difficult due to the specular and noisy nature of these images. Algorithms that claim to automatically classify ultrasonic breast lesions, rely on manual delineation of the tumor boundaries. This is however a slow and cumbersome task. In this work, we combine texture, intensity, gradient and a deformable model along with empirically determined domain specific knowledge to automatically find lesion margins in ultrasound images with no human intervention. The system has successfully extracted tumor boundaries in over 30 breast sonograms.

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Automatic boundary extraction of ultrasonic breast lesions

Abstract

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All Science Journal Classification (ASJC) codes

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