# Fuzzy Logic Clears Up Cancer Picture Techniques for Spotting Enemy Tanks in War Are Adapted for Spotting Tumors

By William Allen Post-Dispatch Science | St Louis Post-Dispatch (MO), March 28, 1994 | Go to article overview

# Fuzzy Logic Clears Up Cancer Picture Techniques for Spotting Enemy Tanks in War Are Adapted for Spotting Tumors

William Allen Post-Dispatch Science, St Louis Post-Dispatch (MO)

UNIVERSITY OF MISSOURI researchers are adapting Cold War computer technology to the war on cancer.

James Keller, a professor of electrical and computer engineering at Mizzou, spent 12 years developing computer-vision techniques that help the U.S. military identify tanks in the jungle.

Now he and colleagues are adapting that technology to detect cancer in tissue biopsies and in mammograms used to screen for breast cancer.

"Tanks, tumors - they're both bad," Keller said in an interview last week. "In both cases, you want to find them by separating the object from the background."

To do that, the researchers apply a mathematical theory called "fuzzy logic."

Fuzzy logic has come into its own in the past decade as a way of solving problems where information is vague or incomplete, said Keller, who is president of the North American Fuzzy Information Processing Society.

Japanese manufacturers have adapted it to make video cameras that counter an unsteady hand and washing machines that automatically compute how much soap and washing time any load of laundry needs. Finding An Enemy Tank

Put simply, fuzzy logic is more forgiving than traditional computer vision programs that make decisions based on strict yes-and-no questions.

Take the case of an enemy tank hiding in the jungle and a missile that seeks to make a direct hit on the tank.

A conventional computer-vision program in the incoming missile would classify every piece of the image in the target area as part of either a tank or a tree. But such a simple "true-false" rule often fails to handle the complexity of the real world.

The chances for a direct hit are better with fuzzy logic, Keller said.

Computer vision based on fuzzy logic allows the program to classify pieces of the image as being "sort of like a tree" or "sort of like a tank." It assigns a certain degree of truthfulness to each classification, such as "I'm 30 percent confident that this region is a tank and 80 percent confident that that region is a tree."

The computer waits for all this evidence about the scene to be tallied, and then makes a "judgment" about where the tank is.

This is a much more accurate way of finding the hidden target, said Keller, who worked to develop such a computer vision system for the Air Force and the Electronics & Space Corp. of St. Louis. Detecting Deadly Cells

Now Keller wants to use fuzzy logic to improve ways of finding cancerous features in the human genetic blueprint and the often vague images of cancer tumors in the breast.

Fuzzy logic could be used to scan the human genetic blueprint for abnormalities linked to cancer, Keller said. Such links have begun to turn up as part of the Human Genome Project. The genome project is the massive effort to map out all the human genes - the genetic instructions in the blueprint for human life.

When applied to a cancer test, a fuzzy logic program would start by scanning a biopsy of tissue from a patient where cancer is suspected.

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