Release date: 2007-06-21
New computer image recognition technology is expected to become a medical diagnostic helper Recently, Dr. Aitan Sharon, a computer scientist at the Weizmann Institute in Israel, is working with Dr. Melaf Glenn of the Massachusetts General Hospital to develop a new computer-identified object through hierarchical comparison. method. This technology is expected to give computers a similar image recognition capability to the human brain.
The researchers first let the computer compare each pixel in the image, group it according to the brightness, and then further compare the features according to structure, shape, and so on. As the identification deepens, more and more parameters are compared and more and more complicated. By doing a series of comparisons from low to high, the computer can distinguish objects from the background.
The next step is a more challenging job – identifying objects. In order for the computer to recognize the object that is seen, such as a pair of glasses. The researchers first let the computer decompose the glasses image into different segments, compare it with all the glasses in the database, compare and classify according to different features, and finally find the glasses with the same characteristics from the database to realize the image. The purpose of identification.
With the help of the radiologist Gu Murray of the Affiliated Hospital of Hadassah University in Jerusalem, the researchers used this technique to analyze and identify the brain damage images of MRI scans. The data processing process is the same as the object recognition. The brain image is decomposed into different segments. Each segment is classified according to the characteristics of brightness, structure, shape, position, etc., and then the computer detects different segments to determine whether the region is healthy.
The results showed that 60%-70% of the damaged areas indicated by the computer were consistent with the doctor's judgment. The researchers said the results were encouraging. They plan to further expand the scope of application of this technology, making it a multidisciplinary medical diagnostic assistant.
—— Information from: Science News
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