Hubble Fights Breast Cancer
A unique marriage between Hubble Space Telescope astronomers and cancer researchers has produced an image-processing technique that shows promise in detecting early breast cancer. Employing techniques used to correct the blurry images sent by Hubble prior to the 1993 servicing mission, this method is designed to detect microcalcifications, an early sign of breast cancer. A group of astronomical and medical researchers from the Space Telescope Science Institute (STScI) in Baltimore, Johns Hopkins University, and the Lombardi Cancer Research Center at the Georgetown University Medical Center in Washington, D.C., is testing this technique to detect microcalcifications in digitized mammograms.
Detecting a microcalcification among the background structures in a mammogram is remarkably similar to finding a faint star in a blurry and cluttered telescope image. Dr. Benjamin Snavely, the National Science Foundation's (NSF) program director for advanced technologies and instrumentation in astronomical sciences, noticed that certain medical images of interest to the Lombardi Center were similar to the astronomical images STScI scientists obtained from Hubble.
Dr. Snavely saw promise in teaming the disciplines, and he arranged for a meeting between the Lombardi Center and STScI. "Each group immediately became interested with what the other was doing," said Dr. Snavely. "They struck up a resonance." The collaboration was awarded a $50,000 grant from the NSF.
Using Hubble's image-processing lessons for cancer detection is the silver lining to the story of Hubble's spherical aberration. When the now-corrected flaw in Hubble's primary mirror was discovered, STScI developed a large repertoire of image-processing software to correct for the telescope's loss of dynamic range and spatial resolution. The flaw allowed STScI scientists to become experts in image-processing techniques that they otherwise would not have needed. STScI is funded by NASA to study the data received from Hubble.
STScI's Dr. Robert Hanisch and Dr. Richard White used a three-part image-processing technique to identify calcifications in four separate test cases, two of which were blind. The key step involved variance normalization, a technique the astronomers had advanced much farther than the medical researchers.
The team's techniques should lead to a more unbiased detection of smaller lesions. The conventional method for detecting lesions is through "eyeball" inspection, which carries the risk of human error.
Next, the team plans to run tests against a standard set of digitized mammograms, measuring overall performance in comparison to other methods of microcalcification detection. These tests will also allow the team to determine the size and sensitivity limits necessary for reliable identifications.