Course Information

Course Name	Turkish	Tıbbi Görüntü Hesaplama
	English	Medical Image Computing
Course Code	BLG 641E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		İlkay Öksüz
Course Objectives		1. A fundamental grounding in the theoretical and practical skills in medical image computing, 2. An understanding of the application of these skills to analyse and extract information from different types of medical images, 3. An overview of the main active research areas in medical image computing, including both a grounding in the theoretical basics and the tackling of practical research problems.
Course Description		Medical Image Analysis, Image Filtering, Image Segmentation, Medical Image Registration, Markov Random Fields, Medical Image Visualization, Deep Learning for Medical Image Computing, Atlases, Image Guided Interventions, Fetal Imaging, Cardiac Imaging, Brain Imaging
Course Outcomes		1. Basic knowledge of the science and role of medical image computing for a range of clinical applications and current imaging modalities 2. Acquired a basic understanding of the important theoretical concepts related to medical image computing 3. Gained understanding and be able to apply medical image analysis and machine/deep learning techniques for classification, segmentation and registration of medical images 4. Gained understanding of the limitations of medical image computing techniques and be able to compare different approaches for practical problems
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