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| TBB5142 | Biomedical Image Processing | 2+2+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of BIOSTATISTICS and MEDICAL INFORMATICS | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Practical | | Contact Hours | 14 weeks - 2 hours of lectures and 2 hours of practicals per week | | Lecturer | -- | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | Learning methods of formation of biomedical images, procesing biomedical images. Archiving and transmitting medical images. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | Forming digital image and two-dimensional signals. | 2,4,6,9,11,13 | 1,3 | | PO - 2 : | Simple image processing algorithms, image segmentation and edge detection. X-Ray image processing. | 1,2,3,6,10,11,12 | 1,3 | | PO - 3 : | Computer Tomography image formation algorithms and Computer Tomograpy image procesing. | 2,3,8,11 | 1,3 | | PO - 4 : | Ultrasonography image processing. | 2 | 1,3 | | PO - 5 : | Information about archiving and transmitting medical images. | 2,4,5,6,9,10 | 1,3 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Image processing applications in medicine. Digital images. Image quality. ROC analysis for evaluating diagnostic capability. Image enhancement and restoration. Image segmentation and classification. Tomographic reconstruction algorithms. 3-D display of organs. Picture archival and communication systems. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | An overview of image processing. What is image processing? Where is it used? | | | Week 2 | Image sources; information about gamma ray, X-ray, ultraviolet, infrared band imaging and etc.. | | | Week 3 | Image improvement, repair, compression, segmentation and other processing information related to these processes. Post code problem sample. | | | Week 4 | Human and Computer Vision. Human detection and test images. | | | Week 5 | Example of digital image; lighting, reflection, gray level, resolution. Checkerboard effect and wrong kontürleme samples. | | | Week 6 | Basic pixel relations, masking process and the general form of geometry. | | | Week 7 | Detailed information about image enhancement. | | | Week 8 | Histogram equalization, image subtraction, image averaging | | | Week 9 | Midterm | | | Week 10 | Spatial filtering, smoothing,. | | | Week 11 | Image segmentation | | | Week 12 | Gradient masks, prewitt, Sobel masks | | | Week 13 | Morphological image processing | | | Week 14 | Erosion, dilation, opening, closing, border removal, thinning, skeleton, etc.. | | | Week 15 | Project prenetation | | | Week 16 | Final exam | | | |
| 1 | Bushberg J. T., Seibert J. A., Leidholdt E. M., Boone J. M., 2002, The Essential Physics of Medical Imaging (2nd Edition), Lippincott Williams and Wilkins, Philadelphia, USA | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 2,00 | 30 | | Project | 15 | | | 20 | | End-of-term exam | 16 | | 1,50 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 13 | 39 | | Arasınav için hazırlık | 15 | 1 | 15 | | Arasınav | 2 | 1 | 2 | | Proje | 2 | 13 | 26 | | Dönem sonu sınavı için hazırlık | 15 | 1 | 15 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 99 |
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