7th Annual STEMtech conference Philadelphia, PA 6 - 9 November, 2016

DESIGN AND CONSTRUCTION OF A MULTIPURPOSE AUTOMATED MICROSCOPE TESTING DEVICE 

Learning process: Microscope (Optical Systems) Diode Laser (how Laser light operates) Camera (how the image is transferred into digital data) Computer/Image processing (how to deal with images)

GaAlAs Laser Diode GaAlAs laser diode used to illuminate the sample with wavelength 0.645μm Laser diode have the advantages of small size, low power dissipation , low cost , low noise, and long life

Image Formation in OLM GaAlAs laser diode

Border Finding Algorithm

(Microscopic images from the video Capture Card) Source Image (Microscopic images from the video Capture Card) Image Enhancement Color Segmentation Data Reduction Object Localization Border Image 3-D representation of the results

Effect of applying the Median filter to the image 100   Image before applying the median filter X-axis of image (Pixel) Y-axis of the image (Pixel) 50 100 150 200 20 40 60 80 120 140 160 180 Median Filter applied to the image

* n: is he number of rows and columns in filter matrix. 50 100 150 200 20 40 60 80 120 140 160 180 50 100 150 200 20 40 60 80 120 140 160 180 2. Canny Edge Detection at n = (S.D.)/1.5 within the color map range [(A.M.) 255]. 1. Canny Edge Detection at n = (S.D.)/2 within the color map range [(A.M.) 255]. Border-Finding Algorithm for five different values of the Adaptive Thresholding method  50 100 150 200 20 40 60 80 120 140 160 180 50 100 150 200 20 40 60 80 120 140 160 180 50 100 150 200 20 40 60 80 120 140 160 180 4. Canny Edge Detection at n = (S.D.)/2 within the color map range [(A.M)+5 255]. 3. Canny Edge Detection at n = (S.D.) within the color map range [(A.M.) 255]. * n: is he number of rows and columns in filter matrix. S.D.: is the Standard Deviation of the sub-image shown in Figure (2b). A.M.: is the Arithmetic mean of the same image. 5. Canny Edge Detection at n = (S.D.)/2 within the color map range [(A.M.)+10 255].

Image with binary object

Wenty Contours of the peaks image. 20 40 60 80 100 120 140 160 180 200 Wenty Contours of the peaks image [Top view] with 4 contour levels Wenty Contours of the peaks image [Top view] with 8 contour levels Wenty Contours of the peaks image [Top view] with 16 contour levels Wenty Contours of the peaks image.

Gray level relief of the basophilic normoblast Without applying mask process Gray level value y-axis of the image (pixel) x-axis of the image (pixel) (b) Applying mask process Gray level value Gray level relief of the basophilic normoblast

-800 -600 -400 -200 200 400 600 800 50 100 150 20 40 60 80 120 140 160 180 x-axis of the image (pixel) y-axis of the image (pixel) (a) x 10-1 (b) Derivative magnitude y-axis of the image (pixel) Gray level relief derivative, after the treatment of the previous Figure with Sobel operator without applying mask process.  

Gray level relief derivative, after the treatment of the sample -800 -600 -400 -200 200 400 600 800 50 100 150 20 40 60 80 120 140 160 180 y-axis of the image (pixel) (a) Gray level relief derivative, after the treatment of the sample with Sobel operator by applying mask process. x-axis of the image (pixel) x 10-1 (b) Derivative magnitude

CASE STUDY

Liver cells with magnification of 150x

Number of Pixels Gray Scale Level

* n : is the number of rows and columns in filter matrix. 1. Canny Edge Detection at n = (S.D.)/2 within the color map range [(A.M.) 255]. 2. Canny Edge Detection at n = (S.D.)/1.5 within the color map range [(A.M.) 255]. 5. Canny Edge Detection at n = (S.D.)2 within the color map range [(A.M.)+10 255]. 3. Canny Edge Detection at n = (S.D.) within the color map range [(A.M.) 255]. 4. Canny Edge Detection at n = (S.D.)/2 within the color map range [(A.M)+5 255]. * n : is the number of rows and columns in filter matrix. S.D. : is the Standard Deviation of the sub-image of the previous slide A.M. : is the Arithmetic mean of the same image.

X-axis of image (pixel) Y-axis of image e (pixel)

Description of the specific feature Type of feature Values Description of the specific feature 1. Area 12198 – Scalar; the actual number of pixels in the region. 2. Centroid [110.156 105.1283] –1-by-2 vector; the x-and y-coordinates of the center of mass of the region. 3. Euler Number 1 – Scalar; equal to the number of objects in the region minus the number of holes in those objects. 4. Bounding Box [48.5 49.5 123 112] –1-by-4 vector; the smallest rectangle that can contain the region. 5. Major Axis Length 133.1557 –Scalar; the length (in pixels) of the major axis of the ellipse that has the same second-moments as the region. 6. Minor Axis Length 121.0161 –Scalar; the length (in pixels) of the minor axis of the ellipse that has the same second-moments as the region. 7. Eccentricity 0.4172 –Scalar; the eccentricity of the ellipse that has the same second-moments as the region. 8. Orientation 11.2364 –Scalar; the angle (in degrees) between the x-axis and the major axis of the ellipse that has the same second-moments as the region. 9. Convex Hull [28x2 double] –p-by-2 matrix; the smallest convex polygon that can contain the region. Each row of the matrix contains the x-and y- coordinates of one vertex of the polygon. 10. Convex Image [112x123 uint8] –Binary image (uint8); the convex hull, with all pixels within the hull filled in (i.e., set to on). 11. Convex Area 12623 – Scalar; the number of pixels in 'Convex Image'. 12. Filled Area – Scalar; the number of on pixels in Filled Image. 13. Extrema [8x2 double] –8-by-2 matrix; the extremal points in the region. 14. Equiv. Diameter: 124.6233 – Scalar; the diameter of a circle with the same area as the region. Computed as sqrt(4*Area/pi). 15. Solidity 0.9663 – Scalar; the proportion of the pixels in the convex hull that are also in the region. Computed as Area/ Convex Area. 16 Extent 0.8855 – Scalar; the proportion of the pixels in the bounding box that are also in the region. Computed as the Area divided by area of the bounding box.

Conclusions

The optical laser microscope (OLM) has the advantages of: The OLM exhibits superior resolution and contrast Microscopes with high amplification is preferable The workstation also provides the following properties: The Histogram provides the Nucleus/Cytoplasm ratio for Histopathologists Simplicity No need of a vacuum system or high voltages No need for specimen charging Being essentially non-destructive accepts image data files in different formats as produced by OLM displays, enhances, and processes the data provide computer control for the location and dimension of the image

Thank you muthanna.al-khishali@humber.ca

http://www.ieee.org/ns/periodicals/Photo/dec2014/index.html