Wavelet-based feature extraction for mammographic lesion recognition

Lori Mann Bruce; Reza R. Adhami

doi:10.1117/12.274165

25 April 1997 Wavelet-based feature extraction for mammographic lesion recognition

Lori Mann Bruce, Reza R. Adhami

Proceedings Volume 3034, Medical Imaging 1997: Image Processing; (1997) https://doi.org/10.1117/12.274165
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States

Abstract

In this paper, multiresolution analysis, specifically the discrete wavelet transform modulus-maximus method, is utilized for the extraction of mammographic lesion shape features. These shape features are used in a classification system to classify lesions as cysts, fibroadenomas, or carcinomas. The multiresolution shape features are compared with traditional uniresolution shape features for their class discriminating abilities. The study involves 60 digitized mammographic images. The lesions are segmented prior to introduction to the classification system. The uniresolution and multiresolution shape features are calculated using the radial distance measure of the lesion boundaries. The discriminating power of the shape features are analyzed via linear discriminant analysis. The classification system utilizes a simple Euclidean distance measure to determine class membership. The system is tested using the apparent and leave-one-out test methods. The results of the classification system when using the multiresolution and uniresolution shape features are classification rates of 83% and 80% for the apparent and leave-one-out test methods, respectively. These results are compared with those of the system when using only the uniresolution shape features. The uniresolution classification rates are 72% and 68% for the apparent and leave-one-out test methods, respectively. Keywords: wavelet transform, multiresolution analysis, feature extraction, classification, shape, mammography, image processing

Citation Download Citation

Lori Mann Bruce and Reza R. Adhami "Wavelet-based feature extraction for mammographic lesion recognition", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); https://doi.org/10.1117/12.274165

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