Here we want to present an easy to use digital inline holographic microscope employing 3D printed parts, a Raspberry Pi and Pi Cam, as well as a high-power LED and a 15 micron pinhole. For details see (link to publication following).
- Print the required parts (.stl files) with a 3D printer or a 3D-printing service of your choice. We used PLA as printer material.
- Using pliers, remove the lens in front of the Raspberry Pi Cam v2. Assemble the Raspberry Pi 3 and the Raspberry Pi Cam.
- Fix the pinhole on the upper side of the pinhole holder. We used black tape to prevent residual light from passing.
- Connect the LED to a current source providing a current of 125 mA. Run the cables through the hole in the lower box. Fix the LED on the lower side of the pinhole holder.
- Assemble lower box, pinhole holder and upper box. Connect the Raspberry Pi Cam to the upper box. Connect a monitor, mouse and power source to the Raspberry Pi. Power it on.
- Open Camera_DIHM.py and insert the experimental parameters. If you run the file, a folder with the name YY.MM.DD_hh.mm will be created and all following files will be saved here. ATTENTION: Run Camera_DIHM.py only once every minute, or the previous files will be overwritten!
- If you control the LED with the Raspberry Pi's GPIO, it will now be turned on. If not, turn on the LED.
- Insert an object on a standard microscope slide. You will now see its hologram in the preview.
- By pressing ENTER an image of the object is captured. If you want to capture a higher number of images, you can enter the number in range(N).
- Remove the object slide. By pressing ENTER again, N in range(N) background images are captured.
- Move the images to a PC with Fiji and the following plugin installed https://unal-optodigital.github.io/NumericalPropagation/
- Open Fiji and the plugin.
- Open the object image and choose Image>Type>32-Bit to convert it to a greyscale image.
- In the Plugin choose the image as real image. Let imaginary image empty. Enter the required parameters.
- Press propagate. After that, you can reconstruct several image planes at once by using Batch. To increase the reconstructed image's contrast you can use Process>Enhance Contrast with (0.2, normalize, prozess whole stack).