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   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 : TBA) 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
3/9/2022 1:42:03 PM