초록

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Abstract ▼ AI-Helper

Medical images are exceedingly important means of diagnosing a variety of diseases and treating patients in current medicine. Advance of the new imaging technologies enables them to acquisite more detailed images. However, the amount of the image data is getting too bigger to analyze the images by o...

Medical images are exceedingly important means of diagnosing a variety of diseases and treating patients in current medicine. Advance of the new imaging technologies enables them to acquisite more detailed images. However, the amount of the image data is getting too bigger to analyze the images by only human visual inspection. Thus, over the past few decades, machine learning has been performing an essential role in the automated medical image analysis. In the paper, we first overview the history, principle, and applications of various medical images thought of as eyes of current medicine. In addition, we introduce the latest techniques of machine learning applied to medical images. For examples, artificial neural network, k-nearest neighbors, genetic algorithm, gaussian mixture model, ant colony optimization, conditional entropy, and fusion of two machine learning algorithms in segmentation, registration, and content-based medical image retrieval.

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