Quantitative evaluation of automatic methods for lesions detection in breast ultrasound images

Karem D. Marcomini; Homero Schiabel; Antonio Adilton O. Carneiro

doi:10.1117/12.2008056

28 February 2013 Quantitative evaluation of automatic methods for lesions detection in breast ultrasound images

Karem D. Marcomini, Homero Schiabel, Antonio Adilton O. Carneiro

Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 867027 (2013) https://doi.org/10.1117/12.2008056
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Ultrasound (US) is a useful diagnostic tool to distinguish benign from malignant breast masses, providing more detailed evaluation in dense breasts. Due to the subjectivity in the images interpretation, computer-aid diagnosis (CAD) schemes have been developed, increasing the mammography analysis process to include ultrasound images as complementary exams. As one of most important task in the evaluation of this kind of images is the mass detection and its contours interpretation, automated segmentation techniques have been investigated in order to determine a quite suitable procedure to perform such an analysis. Thus, the main goal in this work is investigating the effect of some processing techniques used to provide information on the determination of suspicious breast lesions as well as their accurate boundaries in ultrasound images. In tests, 80 phantom and 50 clinical ultrasound images were preprocessed, and 5 segmentation techniques were tested. By using quantitative evaluation metrics the results were compared to a reference image delineated by an experienced radiologist. A self-organizing map artificial neural network has provided the most relevant results, demonstrating high accuracy and low error rate in the lesions representation, corresponding hence to the segmentation process for US images in our CAD scheme under tests.

Citation Download Citation

Karem D. Marcomini, Homero Schiabel, and Antonio Adilton O. Carneiro "Quantitative evaluation of automatic methods for lesions detection in breast ultrasound images", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 867027 (28 February 2013); https://doi.org/10.1117/12.2008056

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available