Instructor: 李夢麟 Meng-Lin Li
Course description:
This is an introductory course of biomedical “imaging” (i.e., designing a
camera which is capable of seeing through human body and small animals) with
emphasis on the signals and systems aspects. It will cover the most important
imaging modalities - projection radiography, X-ray computed tomography,
nuclear medicine imaging, ultrasound imaging, and magnetic resonance imaging.
Basic principles, instrumentation, image characteristics, clinical
applications, and recent progress of these imaging modalities will be
discussed. The students will learn how to apply the knowledge learned in the
course "Signals and Systems" to biomedical imaging.
Prerequisites:
Signals and Systems (at least knowledge of Fourier transform and sampling),
Programming (for computer homework), or consent of the instructor
Topics:
1. Introduction
2. Ultrasound Imaging
3. Magnetic Resonance Imaging
4. X-Ray Imaging
5. X-Ray Computed Tomography
6. Nuclear Medicine Imaging:
Positron Emission Tomography (PET)
Single Photon Emission Computed Tomography (SPECT)
7. Site Visit: We will arrange visits to NTHU Brain
Research Center (and perhaps Mackay Memorial Hospital, Hsinchu).
Textbook:
1. Class notes and related materials will be announced on the NTHU EECLASS
elearning system (http://eeclass.nthu.edu.tw/).
Tentative lecture method:
Powerpoint lecture slides + Asynchrounous on-line lectures + In class Q&A)
References:
1. P. Suetens, “Fundamentals of Medical Imaging,” Cambridge University Press,
2002. (in NTHU library, you can locate the newest version)
2. J. L. Prince, and J. links, “Medical Imaging Signals and Systems,”
Prentice Hall, 2005.
3. A. Macovski, “Medical Imaging,” Prentice Hall, 1983.
4. A. Webb, “Introduction to Biomedical Imaging,” IEEE Press, 2003.
5. K. K. Shung, M. B. Smith, and B. Tsui, “Principles of Medical Imaging,”
Academic Press, 1992.
Note:
It is difficult to find a single textbook which details all of the
aforementioned course materials. Accordingly, we will draw upon other
references (book chapters, research articles, etc.) and internet resources as
needed.
Grading:
60% Computer (MATLAB) and Handwriting Homework
40% Midterm
(Note that these weights are approximate; we reserve the right to change them
later.)
Schedule:
TBA
AI 使用規則: 有條件開放，請註明如何使用生成式AI於課程產出 Conditionally open; please
specify how generative AI will be used in course output
基於透明與負責任的原則，本課程鼓勵學生利用AI進行協作或互學，以提升本門課產出品質。根據
本校公布之「大學教育場域AI協作、共學與素養培養指引」，本門課程採取有條件開放，說明如下
學生須於課堂作業或報告中的「標題頁註腳」或「引用文獻後」簡要說明如何使用生成式AI進行議
題發想、文句潤飾或結構參考等使用方式。若經查核使用卻無在作業或報告中標明，教師、學校或
相關單位有權重新針對作業或報告重新評分或不予計分。
本門課授課教材或學習資料若有引用自生成式AI，教師也將在投影片或口頭標注。
修讀本課程之學生於選課時視為同意以上倫理聲明。