From Images to Answers

Transcription

1 From Images to Answers An Introduction to Image Processing presented by Nick Beavers Applications Specialist Media Cybernetics

2 What is an image? An image is a numerical representation of a picture a set of numbers interpreted by the computer which creates a visual representation that is understood by humans

3 Image: Pixel Array Pixel = Picture Element Pixels are identified by their position in a grid (two-dimensional array), referenced by its row (x), and column (y).

4 Binary Digits (bits) Bitonal 0 = Black 1 = White

5 What is bit-depth? BIT DEPTH is determined by the number of bits used to define each pixel. The greater the bit depth, the greater the number of tones (grayscale or color) that can be represented

6 Bits Tones Binary Digits Array 1 bit (2 1 ) 2 tones 0 or 1 (0 1) 2 bits (2 2 ) 4 tones 00, 01, 10, 11 (0 3) 3 bits (2 3 ) 8 tones (0 7) 000, 001, 010, 011, 100, 101, 110, bits (2 4 ) 16 tones (0 15) 0000, 0001, 0010, 0100, 1000, 0011, 0101, 1001, 1010, 0111, 1011, 1100, 1101, 1110, 1111, 0110

7 Bits Tones Binary Digits Array 8 bit (2 8 ) 256 tones , , etc. (0 255) 12 bits (2 12 ) 4,096 tones (0 4,095) 16 bits (2 16 ) 65,536 tones (0 65,535) 24 bits (2 24 ) 16.7 million tones (0 16,699,999) , , etc , , etc , , etc.

8 Resolution The number of pixels in the image must be sufficient to distinguish features of interest:

9 Resolution Aliasing: Distortion introduced when an image of high resolution is sampled by a detector of lower resolution.

10 Binning 1x mm/pixel 2x mm/pixel 3x mm/pixel 4x mm/pixel Same display settings Different contrast and brightness Images courtesy of Claire M. Brown, PhD, McGill University Department of Biochemistry

11 Over Sampling Zoom mm/pixel Zoom mm/pixel Zoom mm/pixel Zoom mm/pixel Zoom mm/pixel Zoom 1 Zoom 3 Zoom 6 Zoom 8 Zoom 10 Intensity X NA 1.4 Oil Distance (mm) Images courtesy of Claire M. Brown, PhD, McGill University Department of Biochemistry

12 What components are involved in imaging? Input device the source of the images; camera, microscope, scanner, etc Interface hardware the connection between the input device and the computer; takes the input signal and digitizes it for use on a PC Imaging software the user interface to all the imaging components Output devices printers, image storage devices, monitors

13 Types of Imaging Software Capture only or driver software: software used to capture and save an image from a device developed mostly by hardware manufacturers Example: TWAIN drivers Imaging software, Image Editing, Photo Retouching: software used primarily in home and general business applications, mostly consumer oriented Example: Adobe PhotoShop, Microsoft Photo Editor, Image Tools Basic Image Measurement Software: used for basic image capture, enhancement, with simple measuring tools Example: Image-Pro Express General Analytical Image Analysis Software: used in scientific/industrial analysis of images to generate proven data Example: Image-Pro Plus Vertical Market Image Analysis Software: used to solve specific imaging problems in a related industry Example: Array-Pro, Scope-Pro, Materials-Pro Analyzer, or vision software libraries

14 The Analytical Imaging Process Sample Preparation* Acquisition how do we acquire an image into the computer? Enhancement how do we make it look better to extract information? Identification which attributes of the image are we interested in? Measurement what information can we obtain? Report Generation how can we present this information? Archive how can we store the information?

15 Image Enhancement There are basic ways to enhance an image: Modify its intensity index: brightness, contrast, gamma Background correction: flatten, compensate for irregularities Apply a spatial filter or operation: sharpen, low-pass, edge Advanced enhancement Manipulate the image frequencies: Fourier transform Morphological transformations: erode, dilate, both

16 Enhancement: Grey-value Histogram Stretch Low dynamic range Medium contrast Full dynamic range Good contrast

17 Display Intensity Image Enhancement: All Three linear gamma 2 gamma 0.5 brightness contrast All Three Image Intensity Images courtesy of Claire M. Brown, PhD, McGill University Department of Biochemistry

18 Image Enhancement: Background Correction Original Background Automatic flatten of Background

19 Image Enhancement: Spatial Filtering Commonly used convolution filters: Low-pass: blurs, or smoothes an object Sharpen: enhances all intensity transitions Hi-pass: creates harsh intensity variations Median: removes random impulse noise Advanced Filters: Sigma: removes local impulse noise without

20 Sharpen Filter Preview window Filter description Kernel size

21 Image Enhancement: Sharpening Examples

22 Processing / Enhancement Merge Images DAPI Cy3 FITC

23 Processing / Enhancement Extract Images Red Green Blue

24 Extended Depth of Field

25 Tiling Stitching of Images through Automatic Microscope and Stage control

26 Identification Thresholding techniques Identify objects, based on intensity variations from background or other objects of non-interest Grayscale Color Area of Interest (AOI) manually defining regions of interest

27 Thresholding / Segmentation

28 Pre Measurement Steps Object splitting using filters, or manually splitting by drawing lines between touching objects. Guard frame when working on multiple fields side by side, we may need to specify that object touching the borders of the image. Pseudo-color adds false color to the image to show changes in gray values not noticeable to the human eye.

29 Measurement Parameters Size (area, perimeter, length, etc) Shape (roundness, aspect ratio) Density / IOD Clusters Fractal Dimension Uniformity Once objects are identified, we are dealing then with a set of pixels, which are a set of numbers and thus we are able to measure anything as needed

30 Statistical Measurement of Objects

31 Line Profile

32 Thickness Measurements Horizontal section Vertical section Curved section

33 Area Percentage Measurements

34 Fluorescence Measurements Intensities in Time-Series Colocalization

35 Data Output DDE data to Excel for further statistical analysis Create reports single sheet with image, data, charts using a custom template creating a unified and consistent report mechanism for use department wide Data Collector collection of analysis data from multiple images into a single space which can then be used to DDE, or create reports Poster Printing allows for taking a single image and printing it on multiple sheets of paper for presentation/poster sessions Annotation all measurements can be placed onto the image as a layer so it does not interfere with future needs for analysis

36 Data Output

37 Sort Object in Gallery Original measured image Objects sorted by e.g. area

38 Three Dimensional Reconstruction Volume rendering Real Time Interaction Clipping Surface rendering Volume of Interest

39 From Images to Answers Thank You! Nick Beavers Applications Specialist Media Cybernetics

40 From Images to Answers For more information or demo copies please contact: For information on Image-Pro Plus and AutoQuant software please visit: