SBIR-STTR Award

Lp and Nn Based Classifiers for Breast Cancer Diagnosis
Award last edited on: 4/13/21

Sponsored Program
SBIR
Awarding Agency
NIH : NCI
Total Award Amount
$88,595
Award Phase
1
Solicitation Topic Code
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Principal Investigator
Richard P Mignogna

Company Information

Technology Engineering Management Inc

PO Box 16490
Golden, CO 80402
   (303) 279-2271
   N/A
   www.temi.com
Location: Single
Congr. District: 07
County: Jefferson

Phase I

Contract Number: 1R43CA079259-01
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
1998
Phase I Amount
$88,595
Breast cancer is clearly a major public health concern. Currently, the most effective method of detecting breast cancer is mammography. However, while most mammographic abnormalities are benign, they must all be confirmed by additional studies which may include additional mammograms, ultrasound, and biopsy. A computer aided diagnostic (CAD) aide, which can decrease the uncertainty inherent in the evaluation of mammograms, offers the potential of sparing many women the trauma involved in undergoing biopsies to confirm a diagnosis. This SBIR proposal, submitted by Technology/Engineering Management, Inc., describes a research program to establish the feasibility of applying a linear programming (LP) based pattern classifier to the computer aided diagnosis of breast cancer. The ultimate goal of this research is to lay the foundation for a software-based advisor that would serve as a decision aide to the human diagnostician in assessing electronic images of breast tumors, thereby enabling a totally noninvasive diagnosis. Working in conjunction with a research team from the University of Chicago Department of Radiology (UCDR), we plan to evaluate the efficacy of the LP approach to discriminating malignant from benign lesions and compare it to a mammography diagnostic aide that relies on an artificial neural network (ANN) based classifier.Proposed Commercial Applications: This research will form the foundation for a computer aided diagnostic (CAD) system that can be used by radiologists to assist in the diagnosis of mammographic abnormalities. The technique can also be applied to other imaging procedures including magnetic resonance imaging and positron emission tomography.

Thesaurus Terms:
breast neoplasm /cancer diagnosis, computer assisted diagnosis, computer assisted medical decision making, computer program /software, computer system design /evaluation, diagnosis design /evaluation artificial intelligence, bioengineering /biomedical engineering, mammography, neoplasm /cancer classification /staging, noninvasive diagnosis bioimaging /biomedical imaging, human dataNATIONAL CANCER INSTITUTE

Phase II

Contract Number: ----------
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
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Phase II Amount
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