The Robotics and Image Analysis Research Laboratory at UWF


In 1999 alone, 43,300 U.S. women were expected to die from breast cancer.[1] Although mammography is currently the single most effective method of early detection, the National Cancer Institute has increasingly supported interdisciplinary collaboration among scientists, mammographers, and industry to explore the development of better breast imaging technologies.[2] Investigations into automation methods have also been driven by workload issues, as typical screening rates suggest about 1.5-6 cancers will be uncovered for every 1000 films viewed.[3] Research groups in both academia and the commercial sector have responded to this challenge by developing new electronic imaging systems and interpretation aids in the emerging field of digital mammography.

Our research in this area specifically explores the development, utility, and acceptability of computer-based systems than can help to improve radiologists' interpretations of digitized mammogram films. In our system, a digitized version of an X-ray mammogram is processed in a sequence of steps to segment the breast area and enhance abnormal or suspicious regions. The resulting annotated images are then evaluated using ratings by radiologists working at the Ann L. Baroco Center for Women's Health at Sacred Heart Women's Hospital. The images we study are derived from the public database known as the Digital Database for Screening Mammography (DDSM), developed at the University of South Florida. Quantitative assessment of our results is derived from radiologist-marked database ground truth information,

In this research, our goal has not been to make direct comparisons of commercial and academic systems. Alternatively, the focus of this research has been to help to provide a framework for presenting medically relevant issues that can impact the development of digital prompting systems and suggest alternative visualization techniques. Along these lines, we have examined the use of academic outputs alongside outputs provided by the commercially available and FDA-approved R2 ImageChecker M1000 System. As an example, the far left image below shows a digitized mammogram with a malignant abnormality. If detected by the R2 system, a single marker would be placed in this area in the image, prompting a radiologist to examine the area more thoroughly. However, to facilitate such region-of-interest (prompt) understanding, we've found that segmentation images, such as the one shown in the center, appear useful as interpretation aids by enhancing medically relevant features in the prompt areas. Edge-based images such as the one shown on the far right appear useful for facilitating clinical interpretation of possible spicules and for differentiating abnormal and normal tissues. These types of outputs thus have the potential to help mammographers interpret a patient case and guide possible follow-up procedures to fight breast cancer.

Original Image --------- Segmented Image ----- Edge Detected Image


  1. American Cancer Society. Breast Cancer Facts and Figures 1999-2000. Atlanta, GA: American Cancer Society, Inc., 1999.
  2. Breast Cancer Progress Review Group. Chartering the Course: Priorities for Breast Cancer Research, Executive Summary. Bethesda, MD: National Cancer Institute, 1998.
  3. Moore SK. Better breast cancer detection. IEEE Spectrum. New York, NY: IEEE Press, 2001:50-54.

Recent publications related to this project include:

Funding for this project:

Year Agency/Company Nature of Support Amount
1999-2003 The Whitaker Foundation Development and Assessment of Protocols for Efficient Utilization of Large-Scale Digital Mammography Databases
- Support for students, faculty and equipment
[PI: Dr. Melanie A. Sutton]
1999 Council on Undergraduate Research -
Student Summer Research Fellowship in Science and Mathematics
Computer Assisted Diagnosis for Breast Cancer Detection
[Awarded to undergraduate research assistant -- Note: one of only 20 nationally awarded!]
1998-1999 Solutia Inc., with matching funds from the College of Science and Technology Enhancement of Digital Mammograms
1997-1998 Solutia Inc., with matching funds from the College of Science and Technology Database Normalization and Subsampling Techniques for Digital Mammography $2,000

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