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Extracting critical data from medical images based on machine learning

Machine learning can be applied to cancer diagnosis, neurosurgery, radiotherapy, and so on. Its high accuracy and efficiency can improve the hospitals’ overall efficiency and save diagnostic time. This paper aims to provide an algorithm for extracting critical information from x-ray medical images. The extraction process was divided into two parts: 1) the pixel coordinates of cervical vertebra nodes via automatic localization and 2) patient-related data using OCR (optical character recognition). The extracted pixel coordinates and the text information in the image were then validated. Compared with manual processing of medical images, the proposed algorithm in this study provides higher efficiency, which can better serve doctors to evaluate patients’ medical images for further diagnoses. In the future, more and more medical images can be analyzed in a more intelligent and efficient way.