We are developing a deep convolutional neural network (FCN) based cell segmentation method.
We are developing a deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images.
We are developing a treatment outcome prediction method for cancer patients based on radiomics, genomics, and belief function theory.
We are developing a medical image annotation method with a new low-rank modeling-based multi-label active learning.
Welcome to the Medical Imaging and Bioinformatics Lab!
The Medical Imaging and Bioinformatics Laboratory (MIBI) performs research in computational and theoretical image science and pursues the solutions for clinical challenges.
We are working to advance imaging science through the integration of data-driven, machine learning, and physics-based approaches for image formation, image quality assessment, and imaging system optimization. These projects address important needs in clinical medicine and basic biomedical research, such as improved imaging methods for the early detection and management of cancer, tumor and organ motion tracking to address clinical challenges in diagnostic imaging and radiation therapy on cancer patients.
The MIBI is directed by Hua Li, PhD, an assistant professor in the Department of Radiation Oncology at Washington University School of Medicine in St. Louis.