STATISTICAL SURFACE FRACTAL ANALYZER OF BREAST CANCER
DESCRIPTION (Verbatim from the Applicant's Abstract): The applicants will
develop statistical SURFACE fractal dimension (S-fd) features, which will
discriminate benign from malignant breast masses on MRI and mammographic
images. S-fd features derived from three functional representations of breast
mass image data will be evaluated: (1) signal intensity of mass on single MRI
slice; (2) mammographic density of mass on digitized mammogram; (3) thickness
of mass, computed from 3-dim MRI data.
The S-fd features are statistics from Fractal Interpolation Function Models
(FIFM) of breast mass image data. In prior research, FIFM BORDER fd (B-fd)
features were shown to provide more robust discrimination in data-limited
applications such as breast mass analysis than other fd algorithms. FIFM
SURFACE fractals represent multiresolution differences between benign and
malignant masses more accurately and more extensively than FIFM BORDER
fractals, and therefore may provide more reliable discriminatory information.
Robust S-fd features, which discriminate benign from malignant masses, will
have application in computer-aided-diagnosis systems under development.
PROPOSED COMMERCIAL APPLICATION:
The new features will have significant value to the diagnostician who must distinguish
benign from malignant breast lesions. The algorithm is readily integrated into CAD systems
and has potential utility for a variety of medical and industrial applications in texture
analysis of data-limited surfaces.
Small Business Information at Submission:
Principal Investigator:Alan I. Penn
ALAN PENN AND ASSOCIATES, INC.
14 CLEMSON CT ROCKVILLE, MD 20850
Number of Employees: