Difference between revisions of "Team:Cambridge-JIC/MicroMaps"
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− | <p>The purpose of microscopy is to extract some useful information about the specimen: screen for a particular phenotype, examine fluorescence, measure sizes, count cells, recognize distinctive features, eg. nuclei. Focusing on a specimen is just a small part of the art of microscopy. The actual challenge is to interpret the image | + | <p>The purpose of microscopy is to extract some useful information about the specimen: screen for a particular phenotype, examine fluorescence, measure sizes, count cells, recognize distinctive features, eg. nuclei. Focusing on a specimen is just a small part of the art of microscopy. The actual scientific challenge is to interpret the image. Imagine a program that does this for you. This is what we had in mind when creating MicroMaps. To achieve this, we had to implement different types of image processing algorithms. Image recognition is still work in progress, but we believe that we have laid out the framework for a new, smarter, approach to digital microscopy.</p>Stages of image processing: |
− | </p>Stages of image processing: | + | |
Macroscopic scale: - i.e. for use with shapeoko | Macroscopic scale: - i.e. for use with shapeoko | ||
Sample detection – the idea is to be able to detect points of interest (e.g. marchantia samples) with a wide angle camera that has a view of the entire stage. These points would then be stored and the the microscope used to take more detailed images of these. | Sample detection – the idea is to be able to detect points of interest (e.g. marchantia samples) with a wide angle camera that has a view of the entire stage. These points would then be stored and the the microscope used to take more detailed images of these. | ||
− | + | <p><b>The Method:</b> We tested our image processing software on some images of <i>Marchantia</i> gemma on a Petri dish with agar, This was intended to be a step towards our <a href="https://2015.igem.org/Team:Cambridge-JIC/Stretch_Goals" class="blue">Stretch Goal</a> - an automated screening desktop system. Two types of image processing algorithms were implemented:</p> | |
− | + | <ul> | |
− | + | <li><p><b>Standard thresholding.</b><br>This makes an image grey-scale and searches for the dark areas. We started off with a basic contrast increase to isolate the darker areas of the image, which we assume would correspond to samples. Rajiv then followed the steps in a paper by ……… which was supposed to yield much better sample isolation for samples which look faint, and are hard to distinguish from their background. This ended up detecting dents in the agar gel along with the samples. To resolve this issue we came up with the next idea...</p></li> | |
− | + | <li><p><b>Colour detection.</b><br>An eye dropper was added to select the upper and lower colour darknesses to search for (the user would click to select these colours). These colours correspond to areas of the sample with better and worse illumination respectively.Also, a slider that allows you to change the 'darkness' of the sample colour was added. This generally varies depending on room lighting conditions. With this implementation, the program performed much better, detecting the <i>Marchantia</i> gemma before the agar dents.</p></li> | |
− | Microscopic | + | </ul> |
+ | <p><b>Microscopic image processing:</b> | ||
Image stitching is used because we do not have variable zooming options so sometimes cannot see the entire sample in our field of view. We would be able to use this to create a full image of the sample. | Image stitching is used because we do not have variable zooming options so sometimes cannot see the entire sample in our field of view. We would be able to use this to create a full image of the sample. | ||
The colour detection used above could be easily adapted to work with fluorescent samples – this would prove useful for sample counting and detection of, for example, samples that successfully show a specific fluorescent gene. | The colour detection used above could be easily adapted to work with fluorescent samples – this would prove useful for sample counting and detection of, for example, samples that successfully show a specific fluorescent gene. |
Revision as of 14:35, 18 September 2015