PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
BMM 676	MEDICAL IMAGE PROCESSING	3 + 0	1st Semester	7,5

COURSE DESCRIPTION

Course Level	Master's Degree
Course Type	Elective
Course Objective	The aim of this course is to solve basic image processing problems on radiological images such as Magnetic Resonance, Functional Magnetic Resonance, Diffusion MR, Computed Tomography, X-ray, PET, SPECT. Preprocessing, post-processing, filtering, texture analysis, segmentation and some artificial intelligence applications will be performed on images. Applications will be developed in MATLAB and Python programs.
Course Content	Basic concepts, Digital Image Fundamentals, Color transformations and spatial filtering, Filtering in the frequency domain, Image Restoration and Reconstruction, Color image processing, Wavelet Transformation, Morphological Image Processing, Image Segmentation, Object Recognition, Medical Applications-I, Medical Applications-II, Medical Applications-III Medical Applications-IV
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	To learn the fundementals of digital image processing.
2	To learn advanced image processing algorithms and methods.
3	To be able to perform medical applications with MATLAB and Python image processing library.
4	To be able to detect and segment abnormal tissues in medical images.

COURSE'S CONTRIBUTION TO PROGRAM

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Mid-terms	1	56	56
Final examination	1	56	56
Special Study Module (Student)	1	41	41
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

Select Year

	Course Term	No	Instructors
Details	2023-2024 Fall	1	MUHAMMET ÜSAME ÖZİÇ

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
BMM 676	MEDICAL IMAGE PROCESSING	3 + 0	1	Turkish	2023-2024 Fall

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Asts. Prof. Dr. MUHAMMET ÜSAME ÖZİÇ	muozic@pau.edu.tr		TEK A0402-22	%70

Goals		The aim of this course is to solve basic image processing problems on radiological images such as Magnetic Resonance, Functional Magnetic Resonance, Diffusion MR, Computed Tomography, X-ray, PET, SPECT. Preprocessing, post-processing, filtering, texture analysis, segmentation and some artificial intelligence applications will be performed on images. Applications will be developed in MATLAB and Python programs.
Content		Basic concepts, Digital Image Fundamentals, Color transformations and spatial filtering, Filtering in the frequency domain, Image Restoration and Reconstruction, Color image processing, Wavelet Transformation, Morphological Image Processing, Image Segmentation, Object Recognition, Medical Applications-I, Medical Applications-II, Medical Applications-III Medical Applications-IV

Topics

Weeks	Topics
1	Introduction to Medical Image Processing
2	Basic concepts
3	Anaconda, Spyder IDE, OpenCV and Skimage image processing libraries
4	Reading and Writing Images
5	Matrix Operations
6	Color Spaces
7	Morphological Operators
8	Filters
9	Background Subtraction
10	Object Properties
11	Artificial Intelligence and Computer Vision-1
12	Artificial Intelligence and Computer Vision-2
13	Artificial Intelligence and Computer Vision-3
14	Artificial Intelligence and Computer Vision-4

Materials

Materials are not specified.

Resources

Resources	Resources Language
Rafael Gonzales, Paul Wintz, Digital Image Processing, Addison-Wesley Longman Publishing	English
Rafael C. Gonzales, Richard E. Woods, Sayısal Görüntü İşleme, PALME YAYINCILIK	Türkçe

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	50	Final Exam
Midterm Exam	50	Midterm Exam

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

Prospective Student