Category MRD501

This course is intended to enable students to understand the underlying principles of digital image formation and their applications in medical imaging areas. It is structured to acquaint the students with basic understanding and applications of image processing concept, common techniques and mathematical foundations.

At the end of the course, students should be able to:

• Explain the basic theories, concepts and various image processing techniques related to digital image processing.
• Solve problem related to image processing in medical imaging using various image processing techniques.
• Demonstrate teamwork skills through group lab task on digital images, using MATLAB.

Course Syllabus

Topic	Remarks
WEEK 1 (20/3 – 24/4) Course introduction	Lecture: Introduction to the course  Lab 1: MATLAB installation
WEEK 2  27/3 – 31/3) Chapter 1.1 – Introduction to Image processing   • What is digital image • What is image processing • Applications of image processing • Image processing Hardware	Start Entrance Survey (28 Mac-10 April) Textbook:  Chapter 1 & 2  Lecture note 1: Introduction to Image processing Lab 2: (Watch) Complete MATLAB guide Introduction to MATLAB
WEEK 3 (3/4 – 7/4) Chapter 1.2 – Introduction to Image processing • Human visual perception • Image properties • Image aqcuisition • Image type • Spacial & gray-level resolution • Zoom & shrinking	Textbook:  Chapter 2  Start assignment Lecture note 1: Introduction to Image processing Lab 3: (Watch) Lab lesson 1 (Introduction) Download image
WEEK 4 (10/4 – 14/4) Chapter 2.1 – Image Enhancement (Spatial domain) • Histogram processing • Graylevel transformations	Textbook:  Chapter 3  Lecture note 2: Image Enhancement   Lab 4: (Watch) Lab lesson 2 (image fundamental) Download image
WEEK 5 (17/4 – 21/4) Chapter 2.2 – Image Enhancement (Spatial domain) • Image smoothing • Image sharpening	Textbook:  Chapter 3 Lecture note 2: Image Enhancement   Lab 5: (Watch) Lab lesson 3 (image enhancement using point processing operation) Download images
(24/4 – 28/4)	Break – Hari Raya Puasa
WEEK 6 (1/5 – 5/5) Chapter 2.3 – Image Enhancement (Spatial domain) • Logical and arithmetic operations	Lecture note 2: Image Enhancement Lab 6: (Watch) Lab lesson 4 (image enhancement using arithmetric operation) Download images
WEEK 7 (8/5 – 12/5) TEST 1	TEST 1 – (8/5/2023) Lab 7: Basic GUI (Text field & button)
WEEK 8 (15/5 – 19/5) Chapter 3 – Frequency Filtering	Textbook:  Chapter 3  Lecture note 3: Frequency Filtering   Lab 8: (Watch) Lab lesson 5 (Spatial linear filtering) Download images
WEEK 9 (22/5 – 26/5) Chapter 4.1 – Color Processing • Color models • Color segmentation	Submit assignment – (22/5/2023) Textbook:  Chapter 6  Lecture note 4: Color Processing Lecture note 6: Lab 9:  Lab lesson 6 (Derivatives filtering) Basic GUI (Slider) Basic GUI (Pop-up menu)
(29/5 – 2/6)	Semester break Hari Gawai
WEEK 10 (5/6 – 9/6) Chapter 4.2 – Color Processing  • Color smoothing and sharpening	Textbook:  Chapter 6  Lecture note 4: Color Processing Lab 10: (Watch) Lab lesson 7 (Filtering in fourier domain) Basic GUI (Plotting data to Axes) Basic GUI (Insert image to Axes)
WEEK 11 (12/6 – 16/6) Individual project preparation Lab: Group project	Start individual project – (12/6/2023) Start Student Feedback Online (SuFO) (13 June -24 July) Past year paper discussion Lab lesson 8 (Color processing) Lab 11: (Watch lesson 7 and 8) Project preparation and discussion
WEEK 12 (19/6 – 23/6) Individual project preparation Lab: Group project	Past year paper discussion Lab 12: (Watch) Project preparation and discussion
(26/6 – 30/6)	Break – Hari Raya Aidil Adha
WEEK 13 (3/7 – 7/7) Individual project preparation Lab: Group project	Exit Survey (4 -17 July) Past year paper discussion Watch individual project presentation Lab 13:  Project preparation and discussion
WEEK 14 (10/7 – 14/7)	Individual project submission – (14/7/2023)
(17/7 – 21/7)	Study week Exit Student Feedback Online (SuFO) Final examination – (1/8/2023)

Chapter 1.1 – Introduction to Image Processing

Chapter 1.2 – Introduction to Image Processing

Chapter 2.1 – Image Enhancement

Chapter 2.2 – Image Enhancement

Chapter 3.0 – Frequency Filtering

Chapter 4.0 – Color Processing

Assessments

Assignment (20%) – (22/5/2023)

Assignment need to be done by students are the lab assignment based on the 5 lab lessons. All 5 lab assignment need to be submitted at week 9. Please export to .pdf file and upload in the UFuture.

Test (20%) – (15/5/2023)

Test 1 (week 8) only cover chapter 1 and 2. This is close book test. Student will get a set of question and need to submit it within 1 hour.  Write the answer in the question paper. Structure of the test as below:

Objective : 10 questions (10 marks)

Fill in the blank: 10 questions (10 marks)

Short answer: 3 questions (30 marks)

Individual project (20%) – (14/7/2023)

Student need to submit a mini project using Matlab that has GUI (Graphical User Interface) that can modify an image and get some output from that. 

1. The student need to develop a GUI (Graphical User Interface) project during the semester and submit at the end of semester. 
2. The project must contains all of the following features:
   1. Read image file
   2. Convert to grayscale
   3. Convert to binary/BW
   4. Crop the image
   5. Function to enhance the image such as noise filtering, edit contrast and etc (at least 3).
   6. Save the output image in a project file.
3. Submit the project file (.m and .fig) with your 5-10 minutes video (make it short but can cover all) presentation explaining your project. Must include yourself explaining the project.

Final examination (40%) – (1/8/2023)

Date: 1/8/2023

Time: 9.00 AM – 12.00 PM

Duration: 3 Hours

Location: Examination hall

This examination will cover all of the chapters (1-4).

Subjective questions and contain 2 parts:

1. Part A – Objectives – (15 questions – 30 marks)
2. Part B – Short essay – (7 questions – 80 marks)

Hints:

1. List, calculation, define, explain, draw, elaborate, suggest, state, discuss, difference.
2. No coding.
3. Question has more marks need more explanation.