Project Logs

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• RPi-DeviceAdapters

  Kyle M. Douglass • 11/04/2018 at 13:07 • 0 comments

  I am almost finished cleaning up the Micro-Manager cross-compilation tools and adding the documentation. You may find the tools here: https://github.com/kmdouglass/RPi-DeviceAdapters
  

• Cross-compiling the control software

  Kyle M. Douglass • 06/12/2018 at 06:58 • 0 comments

  People within my professional circle know that I really like Micro-Manager for microscope control. Since I know it so well, I chose it as the control software for this project.

  I wrote a blog article recently on how to cross-compile and deploy Micro-Manager onto the Raspberry Pi from a x86_64 laptop. In fact, I now use this "Docker pattern" for building all of my projects that have a very large (> 1 GB) source code footprint.

  I hope you find it useful!
  

  How I built a cross-compilation workflow for the Raspberry Pi
  

• Accessing the R-Pi camera sensor

  Kyle M. Douglass • 08/26/2017 at 21:41 • 0 comments

  To prototype sample mounting and imaging, I need to have very close access to the Raspberry Pi camera sensor. This involved a bit of custom modifications, as I explain in my latest blog post:
  

  http://kmdouglass.github.io/posts/accessing-the-raspberry-pi-camera-image-sensor.html 
  

  I have also finished the laser diode driver circuit with ON/OFF switching controlled by the Pi; I only need a few cables to test it. Once I do, I will post the final design of the driver circuit.
  

• Add noise to image simulations

  Kyle M. Douglass • 07/14/2017 at 06:23 • 0 comments

  My latest blog post is now online. It describes a common mathematical model for camera noise and how to use it to make realistic digital holograms. Videos of noisy holograms are included.

  Ultimately, these will play a role in testing different algorithms for the holographic reconstruction. Enjoy!

  http://kmdouglass.github.io/posts/modeling-noise-for-image-simulations.html
  

• Brief update on laser diode current sources

  Kyle M. Douglass • 07/08/2017 at 20:29 • 0 comments

  I've finally had some time to think about hardware for the lensless imager, specifically the laser diode driver. I learned about the LM317T voltage regulator and how to use it as a constant current source at this site . Circuits based on this regulator seem to dissipate a lot of heat, but their simplicity makes them good starting points.

  Basic holography requires very good light sources with high spatiotemporal coherence. Furthermore, the resolution of the imager will depend on wavelength, with shorter wavelengths giving higher resolutions. Unfortunately, high quality laser diodes that meet these rough specs seem to be a bit pricier than I expected, so I think it would be wise to test out the driver circuit on relatively cheap laser diodes to start. I don't want to buy an expensive laser diode and burn it out because I didn't understand the drive electronics.

  One such cheap component is the ADL 65055TL red laser diode. This is a TO-can packaged laser diode that emits approximately 7 mW of laser light around 655 nm. More importantly, you can buy one of these from Farnell for about USD 3.50, so they would make great test sources.

  I've done some basic calculations for the circuit design and will make a more detailed post once I've bought and tested the parts.

  -kmd
  

• Simulating Inline Holograms with Python

  Kyle M. Douglass • 04/29/2017 at 09:54 • 0 comments

  Before diving right into the hologram inversion code, I wanted create some tools to simulate the creation of holograms that might be recorded by the imager.

  In my latest post, I discuss how to simulate inline holograms from plane waves using Python, including a movie of how the hologram evolves as it propagates away from the target.

  http://kmdouglass.github.io/posts/simulating-inline-holograms.html
  

• Building Micro-Manager on the Pi

  Kyle M. Douglass • 02/10/2017 at 19:01 • 0 comments

  Micro-Manager is an open source platform for controlling microscope hardware, automating image acquisition, and generating metadata about how images are acquired. In biomedical imaging research, it serves as an incredibly important tool because it is free and open source, which means that scientists can benefit from the contributions of others to the software without paying costly licensing fees.

  I recently managed to compile Micro-Manager version 2.0 on the Raspberry Pi. Though I am not yet convinced that Micro-Manager will be the best tool for this particular job given it's relatively heavy footprint on the Pi's slower hardware, it does provide a near ready-made platform to start prototyping acquitistion software for the lensless imager.

  My instructions on how to build MM for the Pi are here: http://kmdouglass.github.io/posts/micro-manager-on-the-raspberry-pi.html#http://kmdouglass.github.io/posts/micro-manager-on-the-raspberry-pi.html#
  

• Networking with the Raspberry Pi

  Kyle M. Douglass • 02/05/2017 at 09:57 • 0 comments

  This log isn't really about the core aim of the project, but it's necessary never-the-less. I just got my Pi and wanted a way to connect to it remotely from my home network. I wanted this because some tasks are more easily performed on my laptop.

  In my recent blog post, I describe how to connect a Pi to my home network and access it via ssh. The link to the post is below.

  Connect a Raspberry Pi to a Home Linux Network
  

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