Fundamentals of Digital Imaging. Dr Paul McMillan Biological Optical Microscopy Platform

Transcription

1 1 Fundamentals of Digital Imaging Dr Paul McMillan Biological Optical Microscopy Platform

2 FIJI/Image J for Beginners Fundamentals of digital imaging The Digital Image (pixels, bit depth) Image Acquisition (dynamic range, resolution, sampling,) Basic Rules of Digital Images (data handling & image ethics) Image Presentation (guidelines, colour sensitivity/blindness & printing) Applications (Demonstrations & hands on sessions) Image Import Image manipulation Annotation Visualisation & presentation of 2D data Visualisation & presentation of 3D data Visualisation & presentation of timelapse data

3 The Digital Image Dr Paul McMillan Biological Optical Microscopy Platform

4 Pixels Your image is recorded as a numerical array of pixels Pixel has its defined - size (sampling resolution) - grey level (bit depth) 100nm 100nm

5 Bit depth 1 bit 2 grey levels bit 4 grey levels bit 8 grey levels bit 16 grey levels 2 4

6 Bit depth intensity coding bit 16bit

7 Bit depth Example images 1-bit 2-bit 3-bit 4-bit 8-bit

8 Bit depth bit 2 bit 3-bit 4-bit 8-bit 50 0

9 Bit depth - equipment Bit depth Grey levels Use BOMP equipment 1 2 Binary masks for image analysis Late night reading NA Scientific cameras, PMT, GaAsP FIJI, Imaris, Metamorph, Volocity PMT, GaAsP (LSM800) Scientific cameras, PMT, HyD PMT, HyD (Leica SP8) 15 32,768 Scientific cameras scmos (OMX) 16 65,536 Scientific cameras, PMT, GaAsP 32 4,294,967,296 FLIM & other high end techniques Visualisation = 8 bit, quantification = 12 or 16 bit PMT, GaAsP (LSM800)

10 Image acquisition Dr Paul McMillan Biological Optical Microscopy Platform

11 Intensity graph Intensity distribution of image x axis = intensity Y axis = # of pixels with that intensity

12 Intensity graph All image modification must be ETHICAL Can adjust Minimum & Maximum position DO NOT adjust gamma (non-linear) Be descriptive of modifications in methods

13 Resolution & Sampling VECTOR RASTER

14 Resolution & Sampling Frame size 3x3 5x5 10x10 20x20 300x300 Pixel size 1/3 =

15 Nyquist rate In order to convert analogue signal to digital, signal needs to be sampled at least 2.3 times of half cycle (from top to bottom) 0.83x 1.3x 2.3x 10x Undersampled Just enough oversampled Image courtesy of Cameron Nowell

16 Nyquist-Shannon sampling Pixel dimensions = Theoretical axial resolution/2.3 Magnification NA Type 405 nm 488 nm 561 nm 633 nm 5 x 0.1 Air x 0.3 Air x 0.5 Air x 1.25 Oil x 1.4 Oil x 1.4 Oil Only use this if you need this resolution

17 Get the best representative image Best representation of what you are seeing on the microscope Crap in Crap out Any staining can be positive or negative depending on your imaging setting - No offset on your raw data - Set range with your (+)/(-) control sample - Same setting between samples - Pilot analysis before/during imaging

18 Basic Rules of Digital Imaging Dr Paul McMillan Biological Optical Microscopy Platform

19 Basic rules of digital data 1. SAVE Always save as the raw file extension.lif or.lei (Leica).lsm or.czi (Zeiss).oif or.oib (Olympus).dv (Deltavision) Raw file Image metadata Metadata contains all image parameters Laser wavelength Light path settings Objective lens / NA Pinhole Frame Size Voxel dimension Gain/offset Bit Depth Scan speed Average

20 Basic rules of digital data 2. Export Raw file Image metadata TIF JPG, GIF, PNG Keeps original information for data analysis Compressed, lossy for PowerPoint only

21 Basic rules of digital data 3. Modification Raw file Image metadata Raw file Image metadata Never process/modify on the raw files. Make a copy to process. 4. Backup Always double back up your data (NHMRC guidelines) Exported Image Exported modified Image Exported Image Exported modified Image Never use the Microscope computer to store your data Data Graphs Modification details Data Graphs Modification details

22 Image = scientific data Image beautification = data manipulation oops, I was not aware of this sorry, but I thought it was okay to make the images clearer

23 Modification on a specific feature Original image Manipulated image -The gold particles have been enhanced -Background dot has been removed Image from Mike Rossner, and Kenneth M. Yamada J Cell Biol 2004;166:11-15

24 Modification on a specific feature Manipulated image? Manipulation revealed By contrast adjustment Cells from other image has been added Image from Mike Rossner, and Kenneth M. Yamada J Cell Biol 2004;166:11-15

25 Modification on a specific feature Original image Manipulated image live with it since it isn t too bad crop it out resection the block and take a new photomicrograph without the tissue fold Image from

26 Modification on the background Original image Manipulated image Acceptable only if - No change occurred in the actual tissue - A statement is made in the figure legend Background Shading in one corner cleaned up Image from

27 Modification on the background Original image Manipulated image uneven illumination & brown fat has been erased NOT Acceptable because -large degree of background alteration (even if it is clarified and the interested area is not modified) Image from

28 Modification to whole image Original image Generally acceptable Misrepresented

29 Modification to whole image (-)Control (+)control sample black GFP expression on the sample looks similar to (+)control exposure and contrast to the maximum Images have not been processed identically Completely black colour balance differs Image from Mike Blatt, and Cathie Martin Plant Physiol. 2013;163:3-4

30 Image presentation Dr Paul McMillan Biological Optical Microscopy Platform

31 Data presentation guidelines Cell Instructions to authors Any alterations should be applied to the entire image. Clearly explain all alterations in the figure legend. Only compare data that are appropriate to compare (e.g., data from the same experiment, acquired the same way). Individual images should not be used in multiple figures (unless the figures describe different aspects of the same experiment) My 5 cents worth Be aware of colour sensitivity & colour blindness Be aware of printing issues

32 Colour (Most) Fluorescence detectors are monochrome Images are usually grayscale Converted to colour using Look Up Tables (LUTs) Blue Green Red 0 255

33 Colour sensitivity

34 RGB RED GREEN BLUE

35 RGB vs CMYK

36 Colours RGB vs CMYK

37 Use grayscale for panels