U.S. Develops New NMR Computation Method to Reduce Scanning Time

U.S. Develops New NMR Computation Method to Reduce Scanning Time MRI is another major advancement in medical imaging after CT. Although it has many breakthrough advantages, it brings more precise technology for medical development and disease diagnosis, but it also has some annoying problems. . The calculation method used by the general nuclear magnetic resonance instrument makes the patient need to stay in the instrument for 45 minutes. Staying in the instrument for a long time may cause some discomfort to the patient and also reduce the equipment usage.

Recently, U.S. researchers have developed a new NMR algorithm that can effectively shorten the examination time. Patients may only need to spend about 15 minutes on the instrument. The new algorithm constructs a benchmark data by inputting information such as the anatomical structure, function, and appearance of different parts, so that the scanning speed is greatly improved. The traditional algorithm requires a continuous scan, and even the information that has been scanned will be reconstructed during the next scan, which will take too long.

Based on the benchmark data, the new algorithm allows the instrument to infer the next image while scanning, and the scanned information does not need to be reconstructed during subsequent scans. Many people will worry that the new algorithm will affect the accuracy of scanning. In fact, the new algorithm does not add too much restrictions, even a special organization can be accurately imaged, although the image quality has a slight impact, but it can make the scan time from 45 minutes To 15 minutes.

However, the new algorithm is still faced with a problem of data processing. It is very difficult for a traditional computer processor to output raw data as an image that doctors can directly read. This may take a long time. Therefore, the new algorithm requires a new computer processor to support it. However, researchers seem to be not too worried about this issue. They think that a computer graphics processor (GPU) may help them to solve this problem. Researchers are actively trying out.

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