Course title
N08104003
Medical Image Processing

 SATOU Hiroki Click to show questionnaire result at 2018

TAKAHASHI Masanobu Click to show questionnaire result at 2017
Course description
In modern society, image processing technology is applied to all fields. This largely depends on the abundant information amount of the image. In this course, after lectures on basic techniques of image digitization and processing, students will learn the principles of medical imaging technologies such as ultrasound, X-ray CT, and magnetic resonance imaging (MRI).
Purpose of class
To understand general image digitization and image processing methods. Further, students will learn the properties and construction principles of representative medical images.
Goals and objectives
  1. Be able to explain basic terms of image processing with full understanding.
  2. Be able to explain basic techniques in image processing.
  3. Be able to explain the principles and characteristics of representative medical imaging technologies with understanding of the significance of medical images.
Language
Japanese
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. About Digital images (Color, Sampling, Quantization) Preparation (Text 1-4, 1-5) 90minutes
Review of the contents 100minutes
2. Geometric transformation. Image filtering and image transformation (1) Preparation (Text 1-3-2, 1-3-3, 1-6-1, 5-1, 5-2) 90minutes
Review of the contents 100minutes
3. Image filtering and image transformation (2). Binary image processing (1) Preparation (Text 5-3, 5-4, 6-1) 90minutes
Review of the contents 100minutes
4. Binary image processing (2). Image segmentation. Video image processing. Pattern detection. Preparation (Text 6-1, 6-3, 6-4, 7-3) 90minutes
Review of the contents 100minutes
5. Pattern recognition, Neural network and deep learning. Input and output equipment (1). Preparation (Text 7-5, 7-5, 9-5) 90minutes
Review of the contents 100minutes
6. Input and output equipment (1). Image file format and recording methods. Preparation (Text 9-5, 9-6) 90minutes
Review of the contents 100minutes
7. Midterm exam and explanations Review of all the contents 190minutes
8. Measurements and Imaging
Ultrasound imaging 		Exercise 30minutes
Survey and discussion on medical imaging 180minutes
9. X-ray imaging Exercise 30minutes
Survey and discussion on medical imaging 180minutes
10. Magnetic resonance imaging (MRI) Exercise 30minutes
Survey and discussion on medical imaging 180minutes
11. Practice of medical image processing: MRI Report 1 180minutes
Survey and discussion on medical imaging 30minutes
12. Deep learning and medical image Exercise 30minutes
Preparation for the final exam 180minutes
13. Final exam and explanations Survey and discussion on medical imaging 180minutes
14. Special lecture Report 2 180minutes
Total. - - 2740minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Midterm exam Final exam Report Total.
1. 25% 25%
2. 25% 25%
3. 40% 10% 50%
Total. 50% 40% 10% -
Evaluation method and criteria
Comprehensive evaluations including quizzes/assignments (5%), and reports (15%) in addition to the results of the mid-term exam (50%) and the final exam (30%) will be conducted.
In addition, the qualification of the image processing engineer examination is taken into the considerations (details will be described first).
The exam will be based on the contents of textbooks, prints, lecture materials, etc.
Students with total evaluation of above 60% earn the credits.
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
Textbooks and reference materials
Visual information processing -Introduction to Computer graphics and Image processing- (CG-ARTS)
Prerequisites
Prepare to be able to understand the program algorithm which was taught in classes such as Information Processing.
Office hours and How to contact professors for questions
  • Takahashi: Friday lunch break.
  • Sato: 5th period of Tuesday (an e-mail appointment is needed in advance).
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
  • Course that cultivates a basic problem-solving skills
Active-learning course
More than one class is interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
Applicable Taking advantage of experience engaged in R&D of biomedical technology at a company, examples of the practical application will be discussed.
Education related SDGs:the Sustainable Development Goals
  • 3.GOOD HEALTH AND WELL-BEING
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Sat Sep 09 07:27:46 JST 2023