Deep Learning-based Biomedical Image Analysis

In the medical imaging and remote sensing field, our research focuses on the development of innovative deep learning and machine learning-based on image analysis techniques. In the biomedical field, for better detection and diagnosis of various human diseases, we are developing a novel deep learning technology with ultrasound and optical images in 2-D and 3-D. Currently, our projects related to the intelligent biomedical image analysis includes deep learning-based spectral image analysis of tumor regions and various skin lesions, 3D semantic segmentation of diseased regions in ultrasound images, time-resolved object tracking and segmentation in various types of biomedical optical images. On the other hand, in the remote sensing field, to generate an automatic digital map, a deep learning network is being constructed for better semantic segmentation of objects in aerial and satellite images. The current projects in the remote sensing field include the development of deep learning models for semantic segmentation of buildings and road and for change detection in aerial and satellite images. For these projects, our lab is collaborating with Dabeeo Inc. and Professor Choi’s Group at DGIST.