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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
1Evaluates the fundamental data structure, imaging characteristics, and intended uses in digital analysis processes of multidimensional MRI and CT images within the context of biomedical engineering research.
2Applies preprocessing, artifact removal, alignment, registration, normalization, and skull-stripping (removal of non-brain structures) procedures on multidimensional radiological images using appropriate methods and software.
3Obtains quantitative findings from neuroimaging data by employing brain atlases, segmentation, surface reconstruction, cortical thickness analysis, and volumetric measurement methods.
4Makes clinical and research-oriented inferences from multidimensional radiological images through voxel-based morphometry, atlas-based classification, and statistical parametric mapping methods.
5Designs radiological image analysis workflows, visualizes analysis results, and interprets them within a scientific/clinical context using relevant software.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12PO 13PO 14
LO 001542444 24123 3
LO 002553555 34233 3
LO 003454554 2423414
LO 004554554 3523414
LO 005445555 2423445
Sub Total232318242422 122191418619
Contribution55455402423414

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