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Winkoms Open Microscopy Team
'Foldscope', the origami microscope
Original source: https://www.mundomicroscopio.com/foldscope/
The Foldscope is a paper microscope equipped with a single lens designed to cost less than $ 1. It is also known as the origami microscope.
This artifact has been developed by Stanford University researcher Manu Prakash.
The main idea is to make a microscope that can be distributed on a large scale in developing countries in order to be used to diagnose diseases.
Manu Prakash realized in 2011 that one of the difficulties in treating diseases such as malaria in the third world was the lack of a clear diagnosis. For the diagnosis of some diseases, a blood test must be performed using a microscope. Unfortunately, this is not an option in many places where lack of money and infrastructure does not allow a microscope.
With the idea of facilitating the diagnostic process, Stanford researchers set out to develop a microscope that was both cheap and highly effective. Thus was born the Foldscope. The microscope structure is constructed from pieces printed with water resistant paper. The remaining elements are a small battery, a lens and an LED light. The sample is inserted into a small slot and then it is possible to observe it with magnifications of up to 500x by bringing the microscope close to the eye.
How does the Foldscope work?
The Foldscope is, at the conceptual level, very similar to the simple microscopes that were manufactured by Anton van Leeuwenhoek during the 17th century. Antonie van Leeuwenhoek was a Dutch cloth merchant who developed a technique to make high quality magnifying glasses. This allowed him to build simple microscopes that achieved increases of an unprecedented level. The Foldscope is based on the same principle but built with much simpler materials and modern manufacturing techniques to reduce its cost drastically.
There are three ways to use the Foldscope. One option is to zoom the lens into the eye to directly observe the sample through the magnifying lens. Another possible option is to connect the Foldscope to a smartphone so that the sample can be seen on a screen. The third option is to project the image of the sample to a white surface thanks to the LED light of the Foldscope.
The Foldscope is small enough to carry in your pocket. This makes it a very practical instrument. Although it is made of very simple materials, it is also very resistant and designed to withstand shocks.
What resolution should my microscope's digital camera have?
Original source: http://www.microscopiaoberta.com/?p=184&lang=ca
The separating power (A.K.A. resolution) of a microscope is not given by the camera but by the objective of the microscope.
It is a classic that our customers ask us for digital cameras of "when more megapixels better" but the reality is that the separating power (A.K.A. resolution) of a microscope is NOT given by the camera but the objective of the microscope
In the market there are microscope cameras from 1 to 32 Megapixels, 5 and 10 Megapixels being usual, but if the separating power / resolution is not given by the camera then how many pixels are necessary to work in microscopy?
First point - The Separating power (A.K.A. Resolution) of a microscope
To determine pixels we need before we must know the separating power of our microscopes.
This parameter is mainly determined by the Numerical Opening of our objectives and is defined by the following simplified formula:
Second point - Nyquist theorem
We already have the resolution of our objectives, but how does it translate into pixels?
To do this, we use the Nyquist Theorem that will determine the ideal pixel size for each of our objectives. A formula for calculating the IDEAL pixel size in microscopy is:
Third point - Camera Sensor Size
Now we know what dimensions it is necessary for our pixels to solve, in maximum detail, the images of our microscopes but we need to translate the size of 1 pixel to the resolutions we use with our cameras.
The simplest formula is:
The simplest way is:
IMPORTANT! Above the obtained megapixel value we will be over sampling the image and we will not get more information. Below the value we lose information and it is not recommended at all.