醫學影像處理
Medical image processing
| 節 | 週五 |
|---|---|
2 09:00–09:50 | 醫學影像處理 EE117 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
The objective of this course is to introduce the students to the fundamental techniques and algorithms used for acquiring, processing, and extracting useful information from digital medical images. Particular emphasis will be placed on covering methods used for image sampling and quantization, image enhancement, edge detection and sharpening, filtering in the spatial domains, image analysis, morphological processing, segmentation, etc. In addition, the students will learn how to apply the methods to solve real-world problems in Python and develop the insight necessary to use image processing tools to solve any new problem.
基礎微積分、線性代數、程式設計;具備撰寫Python程式能力。限研究生以上選修。 本課程於113學年度下學期以中文授課,114學年度上學期將以英文授課,請同學選課時注意,勿重複選課。
課程中講解原理,部分內容將配合原理引導實作,約三小時。請務必準備筆電至本課程。本課程需用到Python,若無程式基礎的同學,需自學基礎Python語法,第三週的Python教學內容,會快速複習本課程所需的部分。 This course has "Theory and Laboratory" components and the students must prepare their laptops for it. This course requires the use of Python. Students without programming experience need to self-study the basic Python syntax. The Python tutorial content in the third week will quickly review the necessary parts for this course, lasting about three hours. Laboratory: All labs require final write-up worksheets and submission of working code to generate your results. The lab worksheet includes the required analysis, images, and information that will be assessed. During lab times, the professor or TA will ask you to demo your code and ask questions about its operation and the results. The labs will consist of theoretical and practical parts and will require the use of Python. Final Project: The project details, data, and requirements will be uploaded to the course website. A four-page (conference-style) write-up, demo, and presentation are assessed. The project will consist of both theoretical and practical components learned from the course and will require the use of Python.
課堂參與-學習單及作業(40%)、期中考試(20%)、期末書面報告(15%)及口頭報告(25%)。
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course description-Overview of medical image processing and Python Introduction |
| 第 2 週 | 和平紀念日 |
| 第 3 週 | Learn coding with Python |
| 第 4 週 | Digital image fundamentals |
| 第 5 週 | Image Enhancement(I) |
| 第 6 週 | Image Enhancement(II) |
| 第 7 週 | 清明節放假 |
| 第 8 週 | Image Filtering(I) |
| 第 9 週 | Image Filtering(II)、segmentation |
| 第 10 週 | 期中考 |
| 第 11 週 | Morphological Processing(I) |
| 第 12 週 | Morphological Processing(Il) |
| 第 13 週 | Application of medical images |
| 第 14 週 | Recognition-a brief of ML |
| 第 15 週 | 端午節 |
| 第 16 週 | Final projects report |
No textbook Reference: Rafael C. Gonzales, Richard E. Woods, “Digital Image Processing”, Third Edition, Pearson Education, 2010.
- 時間
- Appointment by email
- 聯絡方式
- chiayenlee@nycu.edu.tw