The Office of Naval Research’s (ONR) funded software to find and recognize undersea mines is now being applied to help doctors identify and classify cancer-related cells. “The results are spectacular,” said Dr. Larry Carin, Professor at Duke University and developer of the technology. “This could be a game-changer for medical research.”
The problem that physicians encounter in analyzing images of human cells is surprisingly similar to the Navy’s challenge of finding undersea mines. When examining tissue samples, doctors must sift through hundreds of microscopic images containing millions of cells.
To pinpoint specific cells of interest, they are using an automated image analysis software toolkit called “FARSIGHT” funded by NIH and DARPA. FARSIGHT identifies cells based upon a subset of examples initially labeled by a physician. Up to now, the problem has been that the resulting classifications can be erroneous because the computer applies tags based on the small sampling. Also, it can take days even weeks for a pathologist to manually pick out all the endothelial cells in 100 images. The enhanced FARSIGHT toolkit can accomplish the same feat in a few hours with human accuracy.
By adding ONR’s active learning software algorithms, the identification of cells is accurate and FARSIGHT’s performance more consistent, according to the researchers. The enhanced toolkit also requires physicians to label fewer cell samples because the algorithm automatically selects the best set of examples to teach the software.
A medical team at the University of Pennsylvania is applying the ONR algorithms embedded in FARSIGHT to examine tumors from kidney cancer patients. Focusing on endothelial cells that form the blood vessels that supply the tumors with oxygen and nutrients, this research could one day improve drug treatments for different types of kidney cancer.