Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2024 331643 Digital Image Processing 1 3.0 3 ★ Shih-Chun Jin GEOE
IEECSG 10 0 光電三四、光電所和電資外生所合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2024	331643	Digital Image Processing	1	3.0	3	★	Shih-Chun Jin	GEOE IEECSG	10	0	光電三四、光電所和電資外生所合開

Course Plan：

Instructor Shih-Chun Jin

Email a6210647@nycu.edu.tw

Last Updated 2023-12-14 11:23:14

Course Objective The course aims to learn how digital images are practiced in real-world applications, especially in medical images and computer vision. This class will introduce the image's composition, image adjustment, composition, and even feature extraction for radiomics to apply to image detection and recognition. We will introduce some popular image processing algorithms about image processing and implement them in medical imaging projects.

Course Schedule Week Topic Week 1 What is Digital Image Processing-Digital Image Fundamentals Week 2 Introduction to Python environment setting Week 3 Introduction to Medical Image Format Week 4 Intensity Transformations, Spatial Filtering, and kernel function (I) Week 5 Intensity Transformations, Spatial Filtering and kernel function (II) Week 6 Project Report (1) Week 7 Intensity-Based Segmentation Week 8 Morphological Image Processing Week 9 Feature Selection and Classifying Week 10 Project Report (2) Week 11 Fourier Properties and Filtering in the Frequency Domain (1) Week 12 Fourier Properties and Filtering in the Frequency Domain (2) Week 13 Fourier Properties and Filtering in the Frequency Domain (3) Week 14 Project Report (3) Week 15 Image restoration Week 16 Image reconstruction Week 17 Feature extraction, representation, and radiomics for medical Week 18 Project Report (4)

Evaluation and grading policy (1) Homework 40% (2) Project report 40% (3) Participation 20%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Digital Image Process 4/e Gonzalez & Woods

The access to curricular consultation E-mail to a6210647@nycu.edu.tw

The course corresponds to the SDGs

Note
Python programming skills are needed.

Instructor	Shih-Chun Jin
Email	a6210647@nycu.edu.tw
Last Updated	2023-12-14 11:23:14
Course Objective	The course aims to learn how digital images are practiced in real-world applications, especially in medical images and computer vision. This class will introduce the image's composition, image adjustment, composition, and even feature extraction for radiomics to apply to image detection and recognition. We will introduce some popular image processing algorithms about image processing and implement them in medical imaging projects.
Course Schedule	Week Topic Week 1 What is Digital Image Processing-Digital Image Fundamentals Week 2 Introduction to Python environment setting Week 3 Introduction to Medical Image Format Week 4 Intensity Transformations, Spatial Filtering, and kernel function (I) Week 5 Intensity Transformations, Spatial Filtering and kernel function (II) Week 6 Project Report (1) Week 7 Intensity-Based Segmentation Week 8 Morphological Image Processing Week 9 Feature Selection and Classifying Week 10 Project Report (2) Week 11 Fourier Properties and Filtering in the Frequency Domain (1) Week 12 Fourier Properties and Filtering in the Frequency Domain (2) Week 13 Fourier Properties and Filtering in the Frequency Domain (3) Week 14 Project Report (3) Week 15 Image restoration Week 16 Image reconstruction Week 17 Feature extraction, representation, and radiomics for medical Week 18 Project Report (4)
Evaluation and grading policy	(1) Homework 40% (2) Project report 40% (3) Participation 20%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Digital Image Process 4/e Gonzalez & Woods
The access to curricular consultation	E-mail to a6210647@nycu.edu.tw
The course corresponds to the SDGs
Note	Python programming skills are needed.