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Algorithm compares 3D medical images up to 1000x faster

Jun. 21, 2018 – 

Researchers at MIT (Cambridge, MA) have developed a machine-learning algorithm that can make the process of comparing brain scans and other 3D images more than 1,000 times faster than traditional methods.

Medical image registration - the process of transforming different sets of data into one coordinate system - is a common technique that involves overlaying two images, such as magnetic resonance imaging (MRI) scans, to compare and analyze anatomical differences in great detail. For example, doctors can overlap a brain scan from several months ago onto a more recent scan to analyze small changes in a patient's brain, such as the progress of a tumor.

Traditionally, this process has involved meticulously aligning each of potentially a million pixels in the combined scans, and can often take two hours or more. The new machine learning algorithm, however, is able to map all pixels on one image to another all at once.

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