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KMID : 1035520220100020069
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Brain Tumor Research and Treatment : BTRT
2022 Volume.10 No. 2 p.69 ~ p.75
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Artificial Intelligence in Neuro-Oncologic Imaging: A Brief Review for Clinical Use Cases and Future Perspectives
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Park Ji-Eun
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Abstract
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The artificial intelligence (AI) techniques, both deep learning end-to-end approaches and radiomics with machine learning, have been developed for various imaging-based tasks in neuro-oncology. In this brief review, use cases of AI in neuro-oncologic imaging are summarized: image quality improve- ment, metastasis detection, radiogenomics, and treatment response monitoring. We then give a brief overview of generative adversarial network and potential utility of synthetic images for various deep learning algorithms of imaging-based tasks and image translation tasks as becoming new data input. Lastly, we highlight the importance of cohorts and clinical trial as a true validation for clinical utility of AI in neuro-oncologic imaging.
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KEYWORD
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Artificial intelligence, Brain tumor, Deep learning, Imaging genomics
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