1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. BIOMEDICAL ENGINEERING DEPARTMENT
  4. 1507 Biomedical Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
Print

COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
BMM 681NUMERICAL ANALYSIS OF MULTIDIMENSIONAL RADIOLOGICAL IMAGES3 + 01st Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective The aim of this course is to provide students with theoretical knowledge and practical skills in the quantitative analysis of multidimensional medical images such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). The course covers advanced techniques including image preprocessing, artifact removal, registration, coregistration, skull stripping (removal of non-brain tissues), the use of brain atlases, segmentation, normalization, surface reconstruction, cortical thickness analysis, volumetric measurements, atlas-based classification, voxel-based morphometry, and statistical parametric mapping. Students will gain hands-on experience in processing, interpreting, and visualizing both structural and functional neuroimaging data using widely adopted open-source software such as SPM, FreeSurfer, FSL, and 3D Slicer. By the end of the course, students will be equipped with the competencies required to perform clinical and research-oriented analyses in the field of neuroimaging.
Course Content This course covers fundamental and advanced techniques related to the quantitative analysis of multidimensional radiological images such as magnetic resonance imaging (MRI) and computed tomography (CT). The main topics include image preprocessing, artifact removal, registration, coregistration, skull stripping, the use of brain atlases, segmentation, normalization, surface reconstruction, cortical thickness analysis, volumetric measurements, atlas-based classification, voxel-based morphometry, and statistical parametric mapping. The course also includes practical applications using software tools such as SPM, FreeSurfer, FSL, and 3D Slicer.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.

COURSE LEARNING OUTCOMES
1İlk kazanım otomatik olarak atılmaktadır. Güncellemeniz gerekmektedir. Yeni Eklemek için (+) YENİ KAZANIM EKLE tıklayınız.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12PO 13PO 14
LO 001              
Sub Total              
Contribution00000000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Mid-terms15656
Final examination15656
Special Study Module (Student)14141
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


This course is not available in selected semester.


Print

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes