Japanese journal of radiology
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The "democratization of AI" is progressing, and it is becoming an era when anyone can utilize AI. What kind of radiologists are new generation radiologists suitable for the AI era? The first is maintaining a broad perspective regarding healthcare in its entirety. Next, it is necessary to study the basic knowledge and latest information concerning AI and possess the latest knowledge concerning modalities such as CT/MRI and imaging information systems. ⋯ It is an urgent task to nurture human resources by realizing such a healthcare AI education program to educate radiologists at an early stage. If we can evolve to become radiologists suitable for the AI era, AI will likely be our ally more than ever and healthcare will progress dramatically. As we approach the "democratization of AI," it is becoming an era in which all radiologists must learn AI as they learn statistics.
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Deep learning has been developed by computer scientists. Here, we discuss techniques for improving the image quality of diagnostic computed tomography and magnetic resonance imaging with the aid of deep learning. We categorize the techniques for improving the image quality as "noise and artifact reduction", "super resolution" and "image acquisition and reconstruction". For each category, we present and outline the features of some studies.
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Deep learning has been applied to clinical applications in not only radiology, but also all other areas of medicine. This review provides a technical and clinical overview of deep learning in radiology. To gain a more practical understanding of deep learning, deep learning techniques are divided into five categories: classification, object detection, semantic segmentation, image processing, and natural language processing. ⋯ In the medical field, radiologists are specialists in such tasks. Using clinical applications based on deep learning would, therefore, be expected to contribute to substantial improvements in radiology. By gaining a better understanding of the features of deep learning, radiologists could be expected to lead medical development.