image analysis 1 - université laval · image analysis 1 1- introduction to image analysis software...
TRANSCRIPT
Image Analysis 1
1- Introduction to image analysis software “ImageJ”
-development history
-ImageJ vs. Fiji
-installation
-ImageJ website
-sample images
-tour of software environment
2- Basic image analysis using ImageJ:
-opening/saving a file
-file size vs. bit-depth and image-resolution
-calibration
-histograms, “live updates”
-contrast, brightness, saturation
-measurement: linear profiles, statistical information
-Region of Interest (ROI) and local measurements/manipulations
-image calculations 1
http://rsb.info.nih.gov/ijAdapted from : Joel B. Sheffield 2
ImageJ
• An adaptation of NIH image for the Java platform.
• Can run on any computer systems that can run Java (Sun Microsystems)
• Open source
• Two powerful scripting languages
– Java Plugins
– Macro Language
• Continual Upgrades
• Active community of several thousand users
3
ImageJ
• Donc, absence de licence coûteuse.
• Pas Besoin d’être à l’université pour faire ses travaux.
• Un portable est amplement suffisant pour 95% de vos besoins.
• Si on besoin de plus de mémoire pour des analyses c’est possible de utiliser l'un des différents serveurs à Laval.
• Supporte plusieurs types de langage de programmation
• Plugins (Interface permettant d'avoir accès à toute la puissance de java. Idéal pour ajouter de nouvelles fonctions à ImageJ)
4
Resources
5
1. Ferreia, T. et Rasband, W. Ieds) « ImageJ User Guide : IJ1.46r », National Institues of Health,
2012. (lien)
2. Baecker, V. (ed) « Workshop: Image Processing and Analysis with ImageJ », Montpellier RIO
Imaging, 2013. (lien)
3. Miure, K (ed) « Basics of image processing and analysis », Centre for Molecular and Cellular
Imaging EMBL Heidelberg, 2014. (lien)
4. ImageJ Website: http://imagej.nih.gov/ij/
5. Fiji Website: http://fiji.sc/Fiji
1.ImageJ Website: http://imagej.nih.gov/ij/
6
1. Features
2. Documentation ImageJ User Guide
3. Documentation Keyboard Shortcuts
4. Mailing list
5. Downloads example images (get these)
Menus
Introduction to the Main Menu
Of these, we’ll concentrate on:
– Image
– Process
– Analyze
– Plugins
– Help
8
9
L'interface principale
Ouvrir, sauvegarde,
création d'image
Montage,outils de dessin
Modification et conversion,opération
géométrique
Filtres et opérations
mathématiques
Statistiques,Mesures,graphique
Accès aux plugins
Gestion des fenêtres
Raccourcis au site web,
information et mise à jour
Opening and saving files
10
Drag and Drop files onto IJ control strip, or
Open samples
2010-03-18 11
Les Menus (Edit)
Mémoire maximum● Windows 32-bit:
le nombre le plus petit,75% du total ou 1.4 Gbit
● Windows 64-bit:75% du total
● Mac OSX 32-bit:le nombre le plus petit,75% du total ou 1.8 Gbit
● Linux 32-bit: 3 Gbit● Linux 64-bit: illimité
Image Menu
12
Image Menu
13
Demo:
1) Dot blots
Image Menu
14
Demo:
1) M51.tif
Adjust brightness contrast
Saturation?
No! Pixel values do not change.
Process Menu
15
Process Menu
16
Vs.
Math: +6000
Process Menu
17
Vs.
Image Calc.
+
Analyze Menu
18
Analyze Menu
19
Demo:
1) Dot blots
-Measure
-Set measurements
-Changing measurement types and loss of information
2) Embryos
-RGB
Analyze Menu
20
Demo:
1) Results
-Set measurements
-Distribution
-Options (file type for saving)
2) Edit
-Copy data
Analyze Menu
21
Demo:
1) Dot blots
-Log
-Live
-List
-Copy
-Statistics
2) Embryos
-RGB
22
Plugins
• ImageJ peut être considéré comme un
ensemble de petits programmes ou
« plugins » écrit en java.
• Cette structure modulaire à l'avantage de
permettre d'ajouter facilement de nouvelles
fonctions à ImageJ.
• Different versions d’ImageJ ont different
plugins “bundled” ensemble
Plugins Menu
23
24
Enregistrement des commandes de
macro et registre des opérations
Plugins > Macros > Record...
• Enregistre les actions
effectuées et les
transpose en langage
de macros.
• Peut aussi être utilisé
pour laisser une trace
des opérations
effectuées
• Demo
Plugins : information, download
25
Help Menu
26
Opening and saving files
27
Dot_Blot.tif (open sample images)
File size = 141kB
Image Adjust Type
Change to 16-bit
Histogram comparison
Opening and saving files
28
Dot_Blot.tif (open sample images)
File size = 141kB
Image Adjust Type
Apply LUT
Histogram comparison
“Ice”
“fire”
Opening and saving files
29
Dot_Blot.tif (open sample images)
File size = 141kB
Adjust size reduce save
Zoom comparison.
File size comparison
Opening and saving files
30
Dot_Blot.tif (open sample images)
File size = 141kB
Adjust size reduce save
Zoom comparison.
File size comparison
Exercise:
Save as jpg
File size = 7kB
Save back to tiff
File size = 141 kB
Zooming
Pixels, position indicator, intensity value
Opening and saving files
31
Dot_Blot.tif (open sample images)
File size = 141kB
Adjust size reduce save
Zoom comparison.
File size comparison
Exercise:
Save as jpg
File size = 7kB
Save back to tiff
File size = 141 kB
Zooming
Pixels, position indicator, intensity value
Opening and saving files
32
Dot_Blot.tif (open sample images)
Exercise:
1. Save as jpg
File size = 7kB
Do an image subtraction of new file
from original file.
2. Save back to tiff
File size = 141 kB
Do an image subtraction of new file
from original file.
Opening and saving files
33
M51c.tif (open sample images)
Demo:
1. Save as jpg
File size = 4kB
Do an image subtraction of new file
from original file.
2. Save back to tiff
File size = 160 kB
Do an image subtraction of new file
from original file.
Pixel locator/grey value
34
Dot_Blot.tif (open sample images)
Zooming
Pixels, position indicator, intensity value
The Image Histogram
Log Scale
The histogram shows the number of pixels of
each value, regardless of location. The log
display allows for the visualization of minor
components. Note that there are unused pixel
values
35
In this case, the log display indicates that virtually all pixel values are used, even
though they are a small percentage of the total.
Log Scale
36
Brightness Adjustment
The brightness adjustment essentially adds or subtracts a constant to every pixel,
causing a shift in the histogram along the x axis, but no change in the distribution37
Contrast Enhancement
For contrast enhancement, a lower value, in this case, 88, is set at zero, and a higher value, 166, is set at 255. The values of each of the pixels are adjusted proportionately. Note that because of the integer values, not all of the pixel values are used. 38
39
Addition et soustractionProcess > Math > Add...
Original
-125
+125
Addition et soustraction = modifie la brillance de l'image
40
Multiplication et divisionProcess > Math > Multiply...
Original
X 0.5 X 2
Multiplication et division = modifie le contraste de l'image
41
Amélioration automatique du contraste
Process > Enhance Contrast