There are many machine learning solutions and applications that are burgeoning into papers, IPs, and startups. These tools are well suited for detection, segmentation, and classification of disease on medical images. Radiologists perform a combination of these tasks daily using film and computer systems. Dr. Do’s lab is developing medical image machine learning solutions to reduce physicians’ errors and improve patient care.

Presently, high performance computing systems are the most crucial components of the machine learning system. They are relatively inexpensive and very efficient tool in the medical imaging. In addition, there are many open-source algorithms, published network topologies, and pre-trained parameters of neural network. You can also find solutions to error messages or tough questions through online communities.

These novel tools and techniques are a great opportunity for people who are in medical imaging, bioinformatics, and radiology practices to expand their horizons. In this lecture, Dr. Do will discuss three topics: 1) Projects and applications that can be developed and easily implemented. 2) Challenging projects with current technologies and how to overcome them. 3) Exciting new fields that we can tackle together.