Small-data AI and Its Applications to Diagnostic Aid and Virtual AI Imaging
Deep leaning has become one of the most active areas of research in medical imaging. My group has been actively studying on deep learning in medical imaging in the past 25 years, including ones of the earliest deep-learning models for medical image processing, semantic segmentation of lesions and organs, lesion/organ enhancement, and classification of lesions in medical imaging. In this talk, small-data AI that can be trained with a small number of cases is introduced. Our small-data AI was applied to develop AI-aided diagnostic systems (“AI doctor”) and deep-learning-based imaging for diagnosis (“virtual AI imaging”), including 1) AI systems for cancer detection and diagnosis with medical images, and 2) virtual AI imaging systems for separation of bones from soft tissue in chest radiographs and those for radiation dose reduction in CT and mammography. Some of them have been commercialized via FDA approval in the U.S., including the first FDA-approved deep-learning product.
Published on: July 17, 2023
doi: 10.17756/micr.2023-suppl1
Citation: Proceedings of 5th International Conference on Medical Imaging and Therapeutics (Virtual 2023). J Med Imaging Case Rep 7(2): S1-S8.
