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Magnetic resonance imaging

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An anonymous reader writes "According to Wired, 'Today's big data is noisy, unstructured, and dynamic rather than static. It may also be corrupted or incomplete. ... researchers need new mathematical tools in order to glean useful information from the data sets. "Either you need a more sophisticated way to translate it into vectors, or you need to come up with a more generalized way of analyzing it," [Mathematician Jesse Johnson] said. One such new math tool is described later: "... a mathematician at Stanford University, and his then-postdoc ... were fiddling with a badly mangled image on his computer ... They were trying to find a method for improving fuzzy images, such as the ones generated by MRIs when there is insufficient time to complete a scan. On a hunch, Candes applied an algorithm designed to clean up fuzzy images, expecting to see a slight improvement. What appeared on his computer screen instead was a perfectly rendered image. Candes compares the unlikeliness of the result to being given just the first three digits of a 10-digit bank account number, and correctly guessing the remaining seven digits. But it wasn't a fluke. The same thing happened when he applied the same technique to other incomplete images. The key to the technique's success is a concept known as sparsity, which usually denotes an image's complexity, or lack thereof. It's a mathematical version of Occam's razor: While there may be millions of possible reconstructions for a fuzzy, ill-defined image, the simplest (sparsest) version is probably the best fit. Out of this serendipitous discovery, compressed sensing was born.'"

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waderoush writes "In November, Lytro, the maker of the first light field camera for consumers, upgraded its viewer software to enable a feature called 'Perspective Shift.' In addition to refocusing pictures after they've been taken, Lytro audiences can now pivot between different virtual points of view, within a narrow baseline. This 3-D capability was baked into Lytro's technology from the start: 'The light field itself is inherently multidimensional [and] the 2-D refocusable picture that we launched with was just one way to represent that,' says Eric Cheng, Lytro's director of photography. But while Perspective Shift is currently little more than a novelty, the possibilities for future 3-D imaging are startling, especially as Lytro develops future devices with larger sensors — and therefore larger baselines, allowing more dramatic 3-D effects. Cheng says the company is already exploring future versions of its viewer software that would work on 3-D televisions. 'We are moving the power of photography from optics to computation,' he says. 'So when the public really demands 3-D content, we will be ready for it.'"

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Is it worth bluffing if you're playing cards against a computer? Most of us go through the day reading subtle (and some not-so-subtle) social cues, like tone of voice, body language, and facial expressions, to figure out what an appropriate course of action should be. To look into how humans read some of these social cues, researchers have put subjects into an MRI tube and asked them to play a simplified form of poker (just one card) against both computerized and human opponents.

The participants kept track of their opponents' behavior on previous trials when determining whether to bluff with a given card, but were more careful to pay attention to what their human opponents did. The researchers then used MRI images of brain activity to look for areas of the brain that might mediate this difference. One area stood out: the temporal-parietal junction, or TPJ.

(Functional MRI studies have come in for some criticism because the researchers often focus imaging on areas they expect to see involved. In this case, the researchers imaged the whole brain, divided it up evenly, and repeated the search for elevated activity. The TPJ still stood out.)

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[ By WebUrbanist in Conceptual & Futuristic & Technology. ]

Nothing moves faster than light, right? True as that may be in theory, a team at MIT has developed a method for visualizing its propagation to amazing effect in practice.

Slowed down and turned into film format, an illuminated tomato goes from ordinary to uncanny as a snaking arc of white light approaches in a billionth-of-a-second burst, then deforms to move across it, with an unrivaled FPS rate.

And the impact goes beyond making neat little films: “Beyond the potential in artistic and educational visualization, applications include industrial imaging to analyze faults and material properties, scientific imaging for understanding ultrafast processes and medical imaging to reconstruct sub-surface elements.”

So how does it work? Per their abstract: “The effective exposure time of each frame is two trillionths of a second and the resultant visualization depicts the movement of light at roughly half a trillion frames per second. Direct recording of reflected or scattered light at such a frame rate with sufficient brightness is nearly impossible. We use an indirect ‘stroboscopic’ method that records millions of repeated measurements by careful scanning in time and viewpoints. Then we rearrange the data to create a ‘movie’ of a nanosecond long event.”

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