Course title
高次元画像解析特論   [Advanced High Dimensional Image Analysis]
Course category courses for doctoral programs  Requirement   Credit 2 
Department   Year   Semester 3rd 
Course type 3rd  Course code 1080421
Instructor(s)
清水 昭伸   [SHIMIZU Akinobu]
Facility affiliation Faculty of Engineering Office afjgxte/L1151  Email address

Course description
This course treats foundations followed by applications with state of the art technologies about medical image processing and pattern recognition.
Register to google classroom(class code : rfye5ec) in advance.
Expected Learning
You will be able to understand algorithms of medical image analysis and pattern recognition.
Course schedule
1 .Orientation, Display of medical volumes.
2. Gray scale image processing (1) : Smoothing and differential filters
3. Gray scale image processing (2) : Local structure enhancement filters
4. Gray scale image processing (3) : Fast computation of spatial filters
5. Segmentation (1) : Binarization
6. Segmentation (2) : Maximum likelihood
7. Segmentation (3) : Maximum a posteriori
8. Segmentation (4) : Active shape model, Level set based segmentation
9. Segmentation (5) : Sparse modeling based segmentation
10. Segmentation (6) : Graph cuts, Random walk
11. Connected component analysis : Labeling, Thinning etc.
12. Pattern recognition (1) : Bayes decision
13. Pattern recognition (2) : Ensemble learning
14. Pattern recognition (3) : Deep learning
15. Conclusion, Report
Prerequisites
Algebra, Mathematical analysis,Statistical mathematics of liberal arts course
Required Text(s) and Materials
References
Pattern Recognition and Machine Learning, Christopher Bishop
Assessment/Grading
The score is evaluated on the attendance rate and report.
Message from instructor(s)
I hope you understand the essential of medical image analysis.
Course keywords
Image processing, Pattern recognition
Office hours
12:00-13:00, Wednesday
Remarks 1
Remarks 2
Related URL
Lecture Language
Japanese
Language Subject
Last update
8/27/2020 4:44:36 PM