Course syllabus & Schema of work (MRD 501)

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

TopicRemarks
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)

Assessment (MRD 501)

Assessments

  • Assignment (20 % )
    • Assignment : 20 % (Submission deadline 22/5/2023)
  • Test (20%)
    • Test : 20 % (tentative date : 8/5/2023)
  • Individual Project (20%)
    • Project Files : 15 % (Final submission deadline: 14/7/2023)
    • Project video: 5% (Final submission deadline: 14/7/2023)
  • Final Examination (40%)
    • Test : 40 % (tentative date : 27/7/2023) – Dewan peperiksaan

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.