Medical Information Processing

Medical Information Processing

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Major subject

Graduate School of Engineering

1Year

HETMA5MCA1

2.00Credits

講義 (Lecture)

Fall semester 2026

(Fall semester)

Syoji Kobashi

Graduate School of Engineering

Other

Japanese will be the primary language, with English used as needed.

9

Office hours are held on Thursdays from 12:10 to 13:00.
They are conducted via an online meeting system.
Students who wish to attend are required to make an advance appointment through the Q&A function of Universal Passport (unipa).

For questions or inquiries regarding the course, please contact all instructors via the Q&A function on unipa.

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1◎／2〇／3〇

N/a

Ability to keep polishing／Ability to collaborate

[Course Objectives]
This course aims to provide a systematic understanding of medical information used in both clinical and educational settings, including its structure, characteristics, methods of acquisition, and processing techniques. In particular, the course focuses on medical imaging data, clinical data, and medical information systems, and develops fundamental abilities to accurately organize, analyze, and share information, as well as to explain it clearly to others. In addition, the course emphasizes the importance of ethical considerations and information security in handling medical information, and encourages students to cultivate a professional attitude toward continuous learning.

[Learning Outcomes]
Upon successful completion of this course, students will be able to:

1. Organize and explain the main types and characteristics of medical information.
2. Explain basic processing methods for medical imaging data and clinical data.
3. Describe the structure and roles of medical information systems, such as PACS and electronic health records.
4. Identify and explain ethical considerations and information security issues involved in handling medical information.
5. Collaborate with others to organize and examine case studies related to medical information processing, and clearly express their own ideas.

[Subtitle]
Medical Information Processing for Understanding and Utilizing Medical Data

[Keywords]

• Medical Information 
• Medical Imaging 
• Medical Information Systems 
• Information Security 
• Medical AI and Imaging Principles

[Course Description]
This course provides a systematic study of medical information processing technologies, from fundamental concepts to practical applications, with a focus on computer-aided diagnosis systems and software as medical devices. First, students will acquire foundational knowledge of ethics, privacy, and information security, which are essential for handling medical data. Next, the course covers medical information systems, including electronic health records (EHR) and personal health records (PHR), from the perspectives of hospital information networks and medical data standardization. Furthermore, students will study the fundamentals and applications of medical image processing, as well as the use of artificial intelligence and machine learning in the medical field, with the aim of understanding the overall landscape and practical utilization of medical information processing technologies.

[Course Schedule]

1. Computer-Aided Diagnosis Systems and Software as Medical Devices
   Students will organize the position and role of computer-aided diagnosis technologies within the overall framework of medical information processing.
2. Ethics, Privacy, and Security of Medical Data
   Students will organize the ethical and institutional constraints that form the basis for handling medical information.
3. Personal Health Records (PHR), Medical Data Standardization, and HIE
   Students will organize the mechanisms by which medical information is shared and linked, as well as the concepts of standardization that support such processes.
4. Hospital Information Systems (HIS) and Electronic Health Records (EHR)
   Students will organize the flow of information in clinical settings from the perspective of system architecture.
5. Data Warehousing (DWH)
   Students will organize the basic infrastructure for storing and managing medical data in a form suitable for analysis.
6. Real-Time Monitoring Systems, Genomic Medicine, and Data Analysis
   Students will organize the characteristics of information processing for time-sensitive and highly individualized medical data.
7. Medical Data Mining and Predictive Analysis
   Students will organize the fundamental analytical approaches used to derive insights from medical data.
8. Fundamentals of Image Data, Imaging Modalities, and the DICOM Format
   Students will organize how medical images are structured and managed as data.
9. Fundamentals of Medical Image Processing: Gray-Level Transformation and Binarization
   Students will organize the initial processing concepts required to treat image information as numerical data.
10. Morphological Processing and Filtering Techniques
    Students will organize the basic concepts of image processing that focus on shape information and noise reduction.
11. Fundamentals of Region Extraction
    Students will organize the basic ideas for extracting meaningful regions from medical images.
12. Feature Extraction and Representation of Classification Results
    Students will organize how extracted information is represented and used for decision-making.
13. Interpolation, 3D Visualization, and Image Registration
    Students will organize fundamental processing concepts for integrating and handling multiple images.
14. Texture Analysis
    Students will organize perspectives for extracting information based on intensity and texture patterns in images.
15. Medical Applications of Artificial Intelligence and Machine Learning, and Course Summary
    Students will review and summarize the medical information processing technologies covered in this course from the perspective of artificial intelligence applications.

Remote (Fully Online)

This course is conducted fully online.
Classes are delivered in real time using an online conferencing system, and course materials and announcements are distributed via unipa. Students are required to prepare a stable internet connection and an appropriate device to participate.

Limited permission for use

In preparing reports and presentation materials, the use of generative AI is permitted only as a supplementary tool, such as for information gathering, outlining ideas, rephrasing expressions, or refining written text.
However, submitting text or content generated by AI without modification is not permitted. Even when AI-generated outputs are referenced, students must organize and describe the content in their own words based on their own understanding.

Using AI-generated text without proper review or revision, or relying on generative AI for the main substance of an assignment, will be regarded as inappropriate use. In such cases, course credit may not be awarded, or previously awarded credit may be revoked.

No specific textbook is required.
Lecture materials will be distributed in advance via unipa.

Handbook of Medical Imaging Engineering
Supervised by the Japan Society of Medical Imaging Technology,
Edited by the Editorial Committee of the Handbook of Medical Imaging Engineering
ISBN: 978-4-9906667-0-5

Practical Handbook of Medical Image Analysis
Ohmsha, Ltd.
ISBN: 978-4-274-21282-6

【Preparation】

• Students are expected to study the relevant sections of the textbook in advance. Before each lecture, they should review the lecture slides, which will be made available beforehand, to familiarize themselves with the content. The total preparation time for all 15 lectures is estimated to be 30 hours.

【Review】

• Report Writing: Students will complete three reports related to the lecture topics. The total time required for report writing is estimated to be 15 hours.
• Lecture Review: To deepen understanding and reinforce learning, students should review the textbook materials. The total review time is estimated to be 15 hours.

This course actively incorporates active learning approaches. In each class session, time is allocated for questions and interactive discussions, enabling students to think independently and participate actively in the learning process. In addition, brief prompts and discussion activities related to the lecture content are used to check and deepen students’ understanding. Through these activities, the course aims to promote thoughtful and engaged learning rather than one-way acquisition of knowledge.

In this course, students are evaluated comprehensively based on their level of understanding of medical information processing and their ability to analyze and express ideas derived from that understanding. Evaluation emphasizes comprehension of the lecture content, the quality of engagement with assignments, and the ability to think critically and articulate ideas based on what has been learned.

Final grades are determined by the following components:

• Written Reports: 60%
  Students are evaluated on their ability to logically organize and clearly describe their knowledge and understanding of medical information processing in their own words, based on the lecture content. 
• Engagement with Assignments and Comprehension of Course Content: 40%
  Students are evaluated based on the content of their written responses to questions and assignments presented during and after lectures, as well as their expressions of ideas and questions submitted online, with an emphasis on understanding the course material and engaging in independent thinking. 

Please note that submissions involving inappropriate use of generative AI may be excluded from evaluation.

Evaluation results and feedback for written assignments will be individually disclosed via unipa.
In addition, overall tendencies and evaluation criteria will be explained during the course or through unipa.

This course is conducted fully online. Students are required to prepare a stable internet connection and an appropriate device to participate in the course.
Lecture materials and announcements will be distributed via unipa, and students are expected to check them regularly.
As the course covers medical information and medical imaging topics, specialized terminology is frequently used. Students are encouraged to engage in preparatory and review study as needed to ensure adequate understanding of the course content.

Not applicable

The course content and schedule may be partially adjusted within the scope of the course objectives and learning outcomes, depending on students’ level of understanding and learning progress.