Medical Image Computation and the Application

Over the past few decades, medical imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), mammography, ultrasound, and X-ray, have been used for the early detection, diagnosis, and treatment of diseases. In the clinic, medical image interpretation has been performed mostly by human experts such as radiologists and physicians. However, given wide variations in pathology and the potential fatigue of human experts, researchers and doctors have begun to benefit from the machine learning methods. The process of applying machine learning methods in medical image analysis is called medical image computation. We will introduce our work in medical image synthesis, classification, and segmentation. Complementary imaging modalities are always acquired simultaneously to indicate the disease areas, present the various tissue properties, and help to make an accurate and early diagnosis.