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