Imaging Principles in Medical AI
2020/9/7-9/11 14:20-17:20(7、8、9節)
Room 440, Astronomy-Mathematics Building, NTU
Speaker:
Weichung Wang 王偉仲 (NTU)
Cheng Ying Chou 周呈霙 (NTU)
Organizer:
Weichung Wang 王偉仲 (NTU)
Background and Purpose:
This course helps students to learn the basic and latest concepts, algorithms, theories, and implementations in medical imaging. The course also introduces some applications in AI-based medical image analysis.
Outline
• X-ray imaging systems
• Computed tomography (CT): reconstruction mathematics, multidetector CT and its applications
• Magnetic Resonance Imaging (MRI): theoretical basis, imaging techniques and system layout
• Nuclear Medicine: radioisotope imaging, Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET)
• Ultrasound Imaging Systems
• Medical image data format (Digital Imaging and Communications in Medicine, DICOM)
• Image classification for chest X-ray via deep learning
• Image segmentation on 3D CT images via deep learning
• Image registration on 3D CT and MR images via geometry and optimization
Grading
上課時間：2020/9/7-11 第七八九節
課堂參與，小考或作業：30%，個人或小組計畫：70%