CLASSIFICATION OF MAMMOGRAPHIC MICROCALCIFICATION

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$49,984.00
Award Year:
1992
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
19123
Agency Tracking Number:
19123
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
5162 Blazer Pkwy, Dublin, OH, 43017
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Alok Sarwal
(513) 426-6900
Business Contact:
() -
Research Institute:
n/a
Abstract
MASS SCREENING USING MAMMOGRAPHY IS, AT PRESENT, THE ONLY VIABLE AND EFFECTIVE METHOD TO DETECT BREAST CANCER. IT IS DIFFICULT, HOWEVER, TO DISTINGUISH BETWEEN BENIGN AND MALIGNANT MICROCALCIFICAITONS ASSOCIATED WITH BREAST CANCER. THIS DIFFICULTY RESULTS IN A SIGNIFICANT INCREASE IN THE NUMBER OF BIOPSY EXAMINATIONS. MOST OF THE MINIMAL BREAST CANCERS ARE CURRENTLY DETECTED BY THE PRESENCE OF MICRO-CALCIFICATIONS. THE MAJOR PROBLEMS ARE THE RELATIVELY LOW-POSITIVE PREDICTIVE VALUE AND THE HIGH FALSE-POSITIVE RATE NECESARY TO MAXIMIZE SENSITIVITY FOR MINIMAL BREAST CANCER DETECTION. IT IS THE LONG-TERM (PHASE I AND PHSE II) OBJECTIVE OF THIS PROJECT TO BE ABLE TO REDUCE THE FALSE-POSITIVE RATE OF BREAST CANCER DETECTION, WHILE MAINTAINING HIGH SPECIFICITY. THE OBJECTIVE OF PHASE I IS TO DEVELOP A COMPUTERIZED ARTIFICAL NEURAL NETWORK-BASED MAMMOGRAM ANALYSIS SYSTEM. BASIC STEPS INCLUDE FEATURE SELECTION FOR THE MICROCALCIFICATION REGIONS IN THE MAMMOGRAMS, DESIGNING AND TRAINING THE NEURAL NETWORK, AND TESTING AND VERIFICATION OF CLASSIFICATION ACCURACY OF NEURAL NETWORK ALGORITHMS. IMAGE STRUCTURE FEATURES WILL BE SELECTED FROM A SET OF MAMMOGRAMS WITH BENIGN AND MALIGNANT MICROCALCIFICATIONS TO PROVIDE GOOD DISCRIMINATION BETWEEN THEM. THE SYSTEM WILL POSSESS THE ABILITY TO ACCURATELY SEGMENT SUCH REGIONS. THIS SYSTEM CAN BE SUBSEQUENTLY REFINED TO PROVIDE HIGH SPECIFICITY.

* information listed above is at the time of submission.

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