課程資訊
課程名稱
基礎生醫影像處理技術
Fundamentals of Biomedical Image Processing 
開課學期
109-2 
授課對象
工學院  醫學工程學研究所  
授課教師
陳中明 
課號
DBME5018 
課程識別碼
528 U0400 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期二A,B,C(18:25~21:05) 
上課地點
 
備註
本課程中文授課,使用英文教科書。限本系大三以上(本系二年級加選時向教師取得授權碼加選)。展書樓606室。
限學士班三年級以上 且 限本系所學生(含輔系、雙修生)
總人數上限:20人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1092DBME5018_ 
課程簡介影片
 
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課程概述

Image processing is a basic tool for biomedical image analysis. Ranging from contrast enhancement to stereotatic surgery, image processing provides various levels of assistance to the biomedical researches and clinical applications. As an introductory course to the biomedical image processing, the aim of this course is to offer the entry-level graduate students the fundamental image processing techniques. The scope of this course will cover the basic transformation techniques, properties of various medical images, image acquisition, processing and rendering. In addition to the regular lectures, the students are required to exploit advanced techniques independently to reinforce learning. It will include one term project and a couple of paper studies.
Actual implementation of the image processing algorithms on the biomedical images will be emphasized in this course. Although it is not a pre-requisite, the students need to use Matlab as the programming tool for the homeworks. There will be about five homeworks for practice. One exam will be given toward the end of the class. The students will be asked to demonstrate the result of the term project by an oral presentation and a written report.

Topics
l Basic Transformation Techniques
l Basics of Medical Images
l Image Acquisition, Sampling, and Quantization
l Image Enhancement
l Image Segmentation
l Image Compression
l Volumetric Image Analysis
l Rendering Techniques 

課程目標
Getting acquainted with the fundamental image processing techniques for medical images 
課程要求
Calculus, matrix computation, Matlab 
預期每週課後學習時數
 
Office Hours
 
指定閱讀
無 
參考書目
Digital Image Processing (3rd Edition), R. C. Gonzalez, R. E. Woods, Prentice-
Hall, 2008.
Digital Image Processing using Matlab (2nd Edition), R. C. Gonzalez, R. E.
Woods, Prentice-Hall, 2009.  
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Homework 
30% 
 
2. 
Midterm 
30% 
 
3. 
Term Project 
40% 
 
 
課程進度
週次
日期
單元主題
第1週
2/23  Introduction
(核心能力:2,3,4) 
第2週
3/02  Introduction to Medical Imaging & Biomedical Image Processing
(核心能力:2,3,4) 
第3週
3/09  Image Acquisition, Sampling, and Quantization
(核心能力:2,3,4) 
第4週
3/16  Intensity Transformations and Spatial Filtering I
(核心能力:2,3,4) 
第5週
3/23  Intensity Transformations and Spatial Filtering II.
(核心能力:2,3,4) 
第6週
3/30  Practical Points of Deep Learning for Medical Imaging
(核心能力:2,3,4) 
第7週
4/06  Image Enhancement
(核心能力:2,3,4) 
第8週
4/13  Term project proposal 
第9週
4/20  Filtering in the Frequency Domain.
(核心能力:2,3,4) 
第10週
4/27  Midterm 
第11週
5/04  Morphology, Image Segmentation I
(核心能力:2,3,4) 
第12週
5/11  Morphology, Image Segmentation I
(核心能力:2,3,4) 
第13週
5/18  Image Restoration I
(核心能力:2,3,4) 
第14週
5/25  Image Restoration II, Geometric Transformation.
(核心能力:2,3,4) 
第15週
6/01  Image Segmentation III
(核心能力:2,3,4) 
第16週
6/08  Examples of Deep Learning for Medical Imaging
(核心能力:2,3,4) 
第17週
6/15  Term project oral presentation