From Multidisciplinary Computional Anatomy
- 2017年10月24日（水） 14:45 - 16:15
- 名古屋大学 IB電子情報館北棟7F 工学部071講義室
- Ronald M. Summers, MD, PhD, FSAR
- Senior Investigator and Staff Radiologist
- Chief, Clinical Image Processing Service
- Chief, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory
- Radiology and Imaging Sciences
- National Institutes of Health Clinical Center
- The impact of deep learning on radiology and potential applications to surgery
- Major advances in computer science are beginning to have an impact on radiology. The rapid achievements in performance for object detection in natural images have enabled these impacts.
- There has been an explosion of research interest and number of publications regarding the use of deep learning in radiology. In this presentation, I will show examples of how deep learning has led to :major performance improvements in radiology image analysis, including image segmentation and computer aided diagnosis. These improvements have potential applications to surgery including image guided :therapy and minimally invasive surgery.