CMCI imaging courses

Last Update: 17.Nov. 2008

[basic course][macro course][ImageJ Plugin course]
[List of Students][Documents for Courses]

Aim of the course is to shift up the level of image processing/ analysis knowledge and techniques of EMBL researchers. Three courses with different levels are available.

Overview:

1.      Basics for Scientific Digital Image Processing / Analysis
( slide show of the presentation)  --> wirte to Kota if you want to see the textbook.
3 x 2 hours per course. Next basic courses will be in Dec 3, 5, 6. Place: Room 327.
Maximum number of participants: 15 (filled).

2.      Image J  Macro programming
( slide show of the presentation)  --> wirte to Kota if you want to see the textbook.
3 x 2 hours per course. Place:

      Maximum number of participants: 15.    

3.      ImageJ PlugIn programming (Lecturer: Cihan Cetin)

                   (slide show of the presentation)

Requirements: you must bring  down your own laptop.

Please contact Kota Miura (miura@...) directly if you are willing to attend a course.

Course 1: Basics for Scientific Digital Image Processing / Analysis

Background:                 Basic knowledge on digital image processing and analysis has become indispensable in biology. On the contrary, basic training to deal with images quantitatively is not integrated. Standardized knowledge thus must be propagated as a course to all imaging beginners.

Level:               Beginners

Duration:          Three days, two hours each. Practical works using ImageJ will be given as assignments.

Requirements:   Please bring down your own lap-top computer.

Content:           Digital image files and Quantitative Measurements.

Program Outline:

I (day 1)

I-1 Basics of Basics           

- What is “pixel”?        

Pixel intensity = number: digital image is an nD array of numbers

                  Math functions: add, subtract, multiply, divide

- Look-Up Table

            numbers -> intensity -> monitor

- Image Depth

                  Gray scales       (8bit, 12bit, 16bit, 32 bit)

                  RGB    (RGB splitting, RGB merging)

                  Image Math – calculation using two images

- Image Formats           (Header and Data)

                  Microscopy formats

- Compression              (Don’t Compress scientific images)      

- Resizing                     (Shrinking and Enlarging)

I-2 Intensity

      - Histogram

      - Region of Interest (ROI)

                  Intensity measurement

Protein density – intensity, saturation

      - Image correlation between two images

co-localization plot

-         Transformation                  

Contrast Enhancement

Thresholding, Density Slice                              

I-3 Practical works or ASSIGNMENTS

II (day 2)

II-1  Questions and Answers for the assignment from day1.

II-2  Spatial Filtering

      - Linear image processing: convolutions.

High Pass/ Low Pass Filtering

Examples: Gaussian, Averaging, Gradient

- Nonlinear Image Processing:

Basic operations:

Median, Dilation, Erosion, Gradient, Opening, Closing,

Derived operators:

Toggle- Mappings, Top-hat

More advanced techniques:

Morphological Reconstruction , Filling Holes, Clear Border objects

II-3  Segmentation:

- Threshold:

Interactive, Otsu, Isodata, Entropy

Limitations of global threshold methods

- Background subtraction.

- Watershed algorithm

II-4  Feature extraction:

- Binary features (features on a binary set)

- Grey level features (features based on a grey scale image)

II-5  Practical works or ASSIGNMENTS

III (day 3)

III-1  Q & A for the assignment from day2.

III-2 Particle Analysis

                        - semi-automatic measurement of particle number, shapes, intensity

III-3  Dynamics / Motion Analysis

                        - image stacks              (handling)

                        - measuring dynamics: FRAP example

- Z (T) projection         maximum, minimum, average, remove noise, leave tracks…

                        - kymographs

                        - manual tracking          (using plugin)

                                    Calculation of average velocity

Practical works or ASSIGNMENTS

Course 2: Macro programming with ImageJ

Background:    Routine operations can be done automatically when a program using a macro, which is equipped in most of imaging software, is written. Here, we use ImageJ to learn basics on how to write macros for semi-automatic processing of digital image files.   

Level: Intermediate

Duration: Three days with  two hours each. Homework will be assigned to get used to do programming.

Requirements:   Please bring down your own lap-top computer (Please install ImageJ or update to the latest version before coming to the course).

Content: Scripting Quantitative Measurements.

1.      merits of writing macro

2.      Macro „Hello World“

3.      Command Recorder

4.      Getting variables and strings from the user

5.      Loops: while, for

6.      if – else

7.      processing stacks

8.      File I/O

9.      batch processing

Assignments

Course 3: ImageJ PlugIn Development – JAVA programming (3 days course by Cihan Cetin)

            Aim: participants learn how to code ImageJ PlugIn.

Documents for Courses

- Measureing Time Lapse Experiments: An Overview  (html)(pdf)
      Resume for a talk, with reference lists and notes.

List of Students

Basic Course

Nov. 27-31, 2006
Antonino Schepis (CBB)
Darren Gilmour (CBB)
Virginie Lecaudey (CBB)
Fatima Verissimo (CBB)
Heiko Runz (CBB)
Maria Mora Corral (CBB)
Marco Marcello (CBB guest)
Minna Poukkula (DB)
Katrien Janssens (DB)
Lucia  Sironi (GE)
Paulo Alves (CBB)

Macro Course