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Classification of Breast Lesions In Ultrasound Imaging

Award Information

Agency:
Department of Health and Human Services
Branch:
N/A
Award ID:
29241
Program Year/Program:
1995 / SBIR
Agency Tracking Number:
29241
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Advanced Applications
416 Hungerford Drive, Suite 20 Rockville, MD 20850
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Woman-Owned: No
Minority-Owned: Yes
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 1995
Title: Classification of Breast Lesions In Ultrasound Imaging
Agency: HHS
Contract: 1 R43 CA67736-01,
Award Amount: $100,000.00
 

Abstract:

We will develop a computer-assisted system to improve the ability of breast sonography to distinguifrom benign lesions. These are lesions originally detected by mammography and sent to ultrasound forThe lesions are biopsied when they are classified by ultrasound as solid or indeterminate, even thoubenign at biopsy. Because of the large numbers of breast biopsies being performed, even a small improf ultrasound to distinguish benign from malignant could result in significant decreases in numbershealth care costs, and patient morbidity. Our approach is to apply advanced image analysis techniquelesion images. In this Phase I project, we will analyze each lesion for three zones: background textand lesion itself rather than convention methods using one zone. The artificial neural network willfeatures for the classification of the malignancy of the lesion. A newly developed artificial visualconstructed specifically for ultrasound images. This neural network, which simulates human eye, willexperienced sonographers and will be tested for the analysis of ultrasound breast lesions. In Phasepossible features and analytical techniques, test our methods on a large database, and develop automworkstation to make the system usable in a clinical environment.

Principal Investigator:

Minze Chien
30140

Business Contact:

Small Business Information at Submission:

Advanced Applications
416 Hungerford Drive, Suite 20 Rockville, MD 20850

EIN/Tax ID:
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No