博士论文答辩：基于深度学习的生物医学和自然图像恢复与合成研究
日期：2023/05/18 - 2023/05/18
博士论文答辩：基于深度学习的生物医学和自然图像恢复与合成研究
主讲人：Da He, Ph.D. candidate at UM-SJTU Joint Institute
时间：2023年5月18日（周四）上午12:00
地点：密西根学院龙宾楼403会议室
讲座摘要
Various image degradation factors and limitations may happen to numerous imaging systems and thereby influencing various image-based applications. Therefore, a semi-deep learning method was firstly investigated to restore the out-of-focus fluorescence microscopy images, while the end-to-end deep learning method was studied to improve the imaging quality of photoacoustic microscopy. After discussing well-known degradation tasks, a new image degradation about adherent mist and raindrops was proposed, defined, and handled for natural images in the daily life. In addition, to alleviate the quantity limitation of magnetic resonance imaging data, a conditional image synthesis pipeline was explored to benefit high-level clinical applications.
主讲人简介
Da He received his B.S. degree in Optoelectronic Information Science and Engineering from Nankai University. In 2018, he joined the University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China, as a graduate student. He is interested in biomedical image processing and computer vision.