Medical Image
We develop deep-learning-based medical-specific models for data from multiple medical domains, such as X-ray, CT image, and Electronic Health record (EMR). The tasks involve disease/organ classification, lesion detection, keypoint extraction, and organ segmentation. Our goal is to effectively adopt state-of-the-art deep learning techniques to medical domain studies.
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Medical Image classification,
detection, and segmentation -
Due to a lot of reasons like complexitiy and rise of medical data, AI is increasingly be applied within
medical field and its importance is increasing significantly.
We develop new AI algorithms for medical problem and our goal is to achieve an utmost level of accuracy. Because tiny differences change make huge different result, which can save lives. Therefore, We not only apply our novel knowledge of computer vision and natural language processing, but also collaborate extensively with medical experts, practicing clinicians and clinical researchers of prominent medical institutions such as Seoul National University Hospital(SNUH), Seoul National University Bundang Hospital(SNUBH), Asan Medical Center(AMC), Korea University Anam Hospital(KUAH) etc. to obtain state-of-the-art accuracy. We are especially doing a lot of research on medical image analysis with deeplearning, including disease/organ classification, lesion detection, keypoint extraction and organ segmentation from X-ray, CT, MRI images.