Team:Valencia Biocampus/Devices

From 2013.igem.org

Revision as of 20:46, 1 October 2013 by Nightm4re (Talk | contribs)

Show/hide wiki menu

Devices - Devices Overview

One of the most important parts of our project is the relationship between Drylab and Wetlab, therefore at the beginning we asked ourselves: how can we use modeling to contribute to the overall project? How can the Drylab optimize our lab experiments? And above all, how can we do it useful for the team?

To achieve our goal we had two ideas: the first one was to build a machine to get pictures of the plates and send them to a computer, and the second was to create some software in order to recognize these images, improve them and get useful information from them.

Therefore, the engineers decided to create a sub-team called Devices and divide it into two teams: hardware and software.


iGEM Scanner

Our iGEM Scanner is able to detect and create an image of the concentration of various substrates in order to be analysed afterwards and facilitate the modeling work. Moreover it was created entirely with LEGO!

It may seem unbelievable and unrealizable, but LEGO is no longer only for children: there is a new tool called LEGO Mindstorms that allows users to bring their own constructions to life by programming it in an integrated development environment.

Automatons designed this way, are based on two actions: they can obtain different types of measurements from their surroundings by sensing them, and also perform some work with its engines. There are many sensors that can be used are: sound, colour, proximity, touch, acceleration and light sensor, among other, but this last one was the sensor used to carry out the main function of our machine.

Touch.png        Sound.png        Prox.png        Light.png        Colour.png        Acc.png

Light sensors are composed of a photodiode, an electronic component that converts the light that it receives into either current or voltage, depending on the mode of operation. There exist two: photovoltaic mode, when the voltage supplied is zero and its current and voltage in terminals don't vary much with light intensity; or photoconductive mode, when the voltage supplied is positive and its current is very sensitive to the light intensity. This last state is the most interesting, and the one we used in our machine.

LEGO Mindstorms allows you to program a set of measurements taken by this sensor which spread steadily over time (in our case, less than one-hundredth of a second between two equispaced measurements). Each one of this data will be transformed in a single pixel of the final image. Also, to permit the sensor to move around the whole image (to be scanned), we implemented three engines in order to obtain the two degrees of freedom needed for 2D.
Here you can see some pictures we took of the finished scanner (Tip: Click on each image to open a bigger version of it):


SimuElegans logo

C++Elegans

C++Elegans is a lightweight and easy to use image manipulation and analysis software written in C++. It is cross-platform in part due to the use of the open-source GUI library [http://www.wxwidgets.org wxWidgets]. This means it can be compiled and run in several different Operating Systems, such as Linux, Windows and Mac OSX. It is also open-source which means all the code will be freely available and modifiable under the [http://www.gnu.org/licenses/gpl.html GPL v3.0 License].
C++Elegans is being written as part of our iGEM project and makes use of some useful image analysis algorithms.
One can find the latest binaries of C++Elegans for the different available platforms at sourceforge: Binaries

The complete source code is also freely available at sourceforge: Source code

For any other downloads please refer to the main sourceforge project page: C++Elegans

(Note: For the time being only binaries for Lubuntu 13.04 are available).

C++Elegans is very easy to use thanks to the descriptive menus and the simple graphical user interface. The menu is divided into different categories: File, View, Edit and Help. Each of these menus are subdivided into different sub-menus. The status bar gives information about the tools, the current state of C++Elegans, the zoom factor and the local data & time. The menu bar hierarchy (explained) is as follows:

  • File
    • Open → Opens and loads an image, supported formats are: .bmp, .gif, .png, .jpeg, .jpg, .tga, .tiff, .iff, .pcx, .pnm, .xpm, .ico, .ani and .cur.
    • Save → Saves the current image with the same filename (overwrite), supported formats are: .bmp, .png, .jpg, .tga and .tiff.
    • Save As → Saves the current image with a new filename, supported formats are: .bmp, .png, .jpg, .tga and .tiff.
    • Quit → Simply quits C++Elegans, it will remind you of changes made to the image that were not saved.
  • View
    • Zoom Reset → Resets the zoom (Set zoom factor to 100%).
    • Zoom In → Increments the zoom factor.
    • Zoom Out → Decrements the zoom factor.
    • Status Bar → Toggles status bar visibility.
    • Toolbar → Toggles toolbar visibility.
  • Edit
    • Undo → Undo the last action.
    • Redo → Redo the last action.

      As of now the maximum supported undo / redo levels is 32, defined in ScrolledImageWindow.h by the UNDO_LEVELS constant (Thus, one can only change this, currently, at compile time).

    • Colour
      • Invert colours → Inverts the colours of the image. Negative image.
      • Convert to greyscale → Converts the image to greyscale colours.
      • Brightness & Contrast → Allows to change the brightness and the contrast of the image by means of two sliders.
      • Hue, Saturation & Value → Allows to adjust the hue, saturation and value of the image.
      • Automatically adjust value → As its name describes it auto-adjusts the value of the image by means of a simple algorithm.
      • Automatically adjust colours → As its name describes it auto-adjusts the colours of the image by means of a simple algorithm.
      • Automatically adjust levels → As its name describes it auto-adjusts the levels of the image by means of a simple algorithm.
    • Filters → Shows the filters dialog, which allows to apply several different filters to the image with a specific size and as many times as the iterations field indicates. As of now the available filters are:
      1. Median
      2. Mean
      3. Midpoint
      4. Gaussian
    • Edge detection
      • Gaussian → Shows simple gaussian border detection dialog.
      • Sobel → Apply the sobel operator (3x3). $G_x = \left( \begin{array}{ccc} -1 & 0 & 1 \\ -2 & 0 & 2 \\ -1 & 0 & 1 \end{array} \right), G_y = \left( \begin{array}{ccc} -1 & -2 & -1 \\ 0 & 0 & 0 \\ 1 & 2 & 1 \end{array} \right) $
      • Prewitt → Apply the prewitt operator (3x3). $G_x = \left( \begin{array}{ccc} -1 & 0 & 1 \\ -1 & 0 & 1 \\ -1 & 0 & 1 \end{array} \right), G_y = \left( \begin{array}{ccc} -1 & -1 & -1 \\ 0 & 0 & 0 \\ 1 & 1 & 1 \end{array} \right) $
      • Scharr → Apply the scharr operator (3x3). $G_x = \left( \begin{array}{ccc} -3 & 0 & 3 \\ -10 & 0 & 10 \\ -3 & 0 & 3 \end{array} \right), G_y = \left( \begin{array}{ccc} -3 & -10 & -3 \\ 0 & 0 & 0 \\ 3 & 10 & 3 \end{array} \right) $
      • Canny → Shows the canny edge detection dialog.
  • Help
    • Help → Shows the help dialog which contains the C++Elegans documentation.
    • About → Information about C++Elegans, version, credits, license, etc.


Click on each image to open a bigger version of it in a new tab:

C++Elegans Thumbnail #1
As mentioned before, C++Elegans and its complete source code is freely available under the GPL license, which can be found here:
[http://www.gnu.org/licenses/gpl.html GPL v3.0 License]

SimuElegans logo

SimuElegans

SimuElegans is a simple simulation and visualization program written in C++. It is cross-platform and only makes use of standard C++ libraries and the Open Source Graphics Library a.k.a [http://www.opengl.org/ OpenGL]. This means it can be compiled and run in several different Operating Systems, such as Linux, Windows and Mac OSX. It is also open-source which means all the code will be freely available and modifiable under the [http://www.gnu.org/licenses/gpl.html GPL v3.0 License].
One can find the latest binaries of SimuElegans for the different available platforms at sourceforge: Binaries

The complete source code is also freely available at sourceforge: Source code

For any other downloads please refer to the main sourceforge project page: SimuElegans

(Note: For the time being only binaries for Windows Vista/7/8 (x64) and Lubuntu 13.04 are available).

SimuElegans is just being used for the sole purpose of visualazing some of our simulations so its usage is straightforward, in the sense that one has to follow the simple on-screen menu.
Click on each image to open a bigger version of it in a new tab:

SimuElegans Thumbnail #1 SimuElegans Thumbnail #2 SimuElegans Thumbnail #3
SimuElegans and its complete source code is also freely available under the GPL license, which can be found here:
[http://www.gnu.org/licenses/gpl.html GPL v3.0 License]

Results

At first the scanner didn't work as well as we expected, the images we took with our scanner were very blurry and noisy at first but then by working hard on the hardware and improving our scanner and also our software, and by putting the scanned images through some of our software noise suppression algorithms we obtained much clearer and detail-rich images. We now proceed to present some of the results we obtained.


Both sequences of images from left to right follow the same pattern:
1. Original image.
2. Image scanned with our first scanner.
3. Image scanned with our second scanner.
4. Image scanned with our third scanner.
5. Image filtered using a 3x3 Median Filter (4 iterations) and a 3x3 Mean Filter (1 iteration) in C++Elegans.
6. Resulting image of applying a Scharr Operator in C++Elegans.


These were obviously early tests, afterwards we obtained some biological results.

C.Elegans tracks & colonies C.Elegans tracks & colonies filtered C.Elegans tracks & colonies hints


The image sequence from left to right is as follows:
1. Scanned image.
2. Image with 3x3 Median filter applied for noise removal and homogeneization.
3. Image with some information added.


Here are some results for C.elegans clumping:

Plate 1 Plate 1 Filtered Plate 1 Scharr Plate 1 Canny Edge Detection Plate 1 Info

Plate 2 Plate 2 Filtered Plate 2 Scharr Plate 2 Canny Edge Detection Plate 2 Info

Plate 3 Plate 3 Filtered Plate 3 Scharr Plate 3 Canny Edge Detection Plate 3 Info



Each sequence of images follows the same pattern:
1. Scanned image.
2. 3x3 Median Filter (1 iteration) applied to get rid of noise.
3. Scharr Operator applied.
4. Canny Edge Detection algorithm applied until non-maxima suppression step (inclusive). (Note: We couldn't finish the algorithm as explained in the notebook).
5. Same image as 4. but with some additional information.