System Bits: Oct. 4

Visible-light-based imaging; game theory; single-chip cancer screening.

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Light deflection through fog
In a development that could lead to computer vision systems that work in fog or drizzle, which have been a major obstacle to self-driving cars, MIT researchers have developed a technique for recovering visual information from light that has scattered because of interactions with the environment — such as passing through human tissue.

This technology — called all-photons imaging — could also lead to medical-imaging systems that use visible light, which carries much more information than X-rays or ultrasound waves.

In experiments, the researchers fired a laser beam through a “mask” — a thick sheet of plastic with slits cut through it in a certain configuration, such as the letter A — and then through a 1.5-centimeter “tissue phantom,” a slab of material designed to mimic the optical properties of human tissue for purposes of calibrating imaging systems. Light scattered by the tissue phantom was then collected by a high-speed camera, which could measure the light’s time of arrival. (Source: MIT)

In experiments, the researchers fired a laser beam through a “mask” — a thick sheet of plastic with slits cut through it in a certain configuration, such as the letter A — and then through a 1.5-centimeter “tissue phantom,” a slab of material designed to mimic the optical properties of human tissue for purposes of calibrating imaging systems. Light scattered by the tissue phantom was then collected by a high-speed camera, which could measure the light’s time of arrival.
(Source: MIT)

To test this, the team fired a laser beam through a “mask” — a thick sheet of plastic with slits cut through it in a certain configuration, such as the letter A  — and then through a 1.5-centimeter “tissue phantom,” a slab of material designed to mimic the optical properties of human tissue for purposes of calibrating imaging systems. Light scattered by the tissue phantom was then collected by a high-speed camera, which could measure the light’s time of arrival. From that, the algorithms were able to reconstruct an accurate image of the pattern cut into the mask.

The imaging technique’s potential applications in automotive sensing may be even more compelling than those in medical imaging because many experimental algorithms for guiding autonomous vehicles are highly reliable under good illumination, but fall apart completely in fog or drizzle. And because computer vision systems misinterpret the scattered light as having reflected off of objects that don’t exist, the researchers believe the technique could address that problem.

Revealing the fragility of common resources through game theory
According to Purdue University researchers, new insights into game theory shows that people are naturally predisposed to over-use “common-pool resources” such as transportation systems and fisheries even if it risks failure of the system, to the detriment of society as a whole — which could have implications for the management of engineered systems such as the power grid, communications systems, distribution systems, and online file sharing systems, along with natural systems such as fisheries.

Shreyas Sundaram, at left, an assistant professor in Purdue University’s School of Electrical and Computer Engineering, and doctoral student Ashish Hota are performing research in game theory that harnesses the Nash equilibrium, developed by Nobel laureate John Nash, whose life was chronicled in the film “A Beautiful Mind.” (Source: Purdue University)

Shreyas Sundaram, at left, an assistant professor in Purdue University’s School of Electrical and Computer Engineering, and doctoral student Ashish Hota are performing research in game theory that harnesses the Nash equilibrium, developed by Nobel laureate John Nash, whose life was chronicled in the film “A Beautiful Mind.” (Source: Purdue University)

The team said this ongoing research harnesses the Nash equilibrium, developed by Nobel laureate John Nash (whose life was chronicled in the film “A Beautiful Mind”), and also applies “prospect theory,” which describes how people make decisions when there is uncertainty and risk.

Shreyas Sundaram, an assistant professor in Purdue University’s School of Electrical and Computer Engineering said, “We are surrounded by large-scale complex systems, and as engineers we are trying to figure out how to design systems to be more robust and secure. One aspect would be how you could engineer systems so that the incentives for people to use them are aligned with perhaps what’s best for society. As a government, what sorts of things can you do to make sure people use systems in a responsible manner?”

Single-chip cancer screening analyzes 10,000 stem cells at once
University of Michigan researchers have developed a new device for studying tumor cells that can trap 10,000 individual cells in a single chip.

The team believes this device could one day help screen potential cancer treatments based on an individual patient’s tumor, and help researchers better understand so-called cancer stem cells. It also sheds light on a controversy: are large cells or small cells more likely to be cancer stem cells?

The channel through the chip splits into 64 branches, each with 200 chambers along it for trapping single cells. (Source: Yoon Lab, University of Michigan)

The channel through the chip splits into 64 branches, each with 200 chambers along it for trapping single cells. (Source: Yoon Lab, University of Michigan)

Euisik Yoon, professor of electrical engineering and computer science, and biomedical engineering said, “Most normal cells will die if they are not anchored to something, but cancer stem cells can survive. They can become circulating tumor cells and come to another area of the body.”

The team led by Yoon created a device that takes advantage of this ability in hopes of understanding cancer stem cells better: how to identify them, what causes them to grow or die, and how to target them with cancer treatments. Their chip contains up to 12,800 wells for catching individual cancer cells. The team tested the chip with breast cancer cells, donated by researchers in the U-M Comprehensive Cancer Center.

While the ability to isolate 10,000 individual cells is impressive, it wouldn’t be useful if the team had to manually record every one, as required by most devices that capture cancer cells. The key is their computer algorithm, capable of combing through the microscope images and assessing the size and number of cells in each well. The algorithm’s particular talent is identifying cells no matter whether they show up dimly or brightly in the microscope image, they said.