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