Reportedly, researchers from Aalto University are developing a brain-imaging device that utilizes a novel type of sensor put on the surface of a person’s head. The novel sensors use quantum optics, facilitating them to decrease the distance amid the brain surface and the sensors to half of what existing MEG (magnetoencephalography) scanners use. Apparently, MEG lets scientists see which parts of the brain are dynamic by calculating the magnetic fields created by electric currents in the brain. At present, MEG scanners utilize superconducting sensors that need to be at particularly low temperatures (just above absolute zero) to work. To maintain them at ultra-cold condition, the sensors need liquid helium that makes MEG scanners huge and expensive.
For protecting the patient’s head from the extreme cold condition, the sensors must be thermally coated keeping them about 2 Cm away from the head. Professor Lauri Parkkonen added, “When the distance amid the brain and the adjacent sensor increases, the magnetic field crumbles and the accurateness of localizing brain activity deteriorates. The sensors that are fitted in existing MEG devices today do not acclimatize to the head’s shape of the individual being screened.” Parkkonen explained the benefits of new sensors and said, “They are very small and can work in the normal room temperature.”
Recently, Aalto University was in news as its study stated that deep learning prototype detects diabetic eye diseases perfectly. As per the research, the deep learning representation detects the severity score of macular edema and diabetic retinopathy accurately. Seemingly, diabetic retinopathy is one of the most ordinary comorbidities of diabetes that—if not treated—might cause severe vision loss. However, macular edema is referred to swelling under a particular part of the retina induced by diabetic retinopathy. The findings were published in Scientific Reports.
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