Desktop CT and 3D Scanner With Arduino

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Introduction: Desktop CT and 3D Scanner With Arduino

About: Projects in light, music, and electronics. Find them all on my site: www.jbumstead.com

Computed tomography (CT) or computed axial tomography (CAT) is most often associated with imaging the body because it enables clinicians to see the anatomical structure inside the patient without having to do any surgery. To image inside the human body, a CT scanner requires X-rays because the radiation has to be able to penetrate through the body. If the object is semi-transparent, it is actually possible to conduct CT scanning using visible light! The technique is called optical CT, which is different than the more popular optical imaging technique known as optical coherence tomography.

To acquire 3D scans of semi-transparent objects, I constructed an optical CT scanner using an Arduino Nano and Nikon dSLR. Halfway through the project, I realized that photogrammetry, another 3D scanning technique, requires much of the same hardware as an optical CT scanner. In this instructable, I will go over the system I constructed that is capable of CT scanning and photogrammetry. After acquiring images, I have steps on using PhotoScan or Matlab for computing 3D reconstructions.

For a full class on 3D scanning, you can check out the instructables class here.

I recently found out about Ben Krasnow built an x-ray CT machine with an Arduino. Impressive!

After posting, Michalis Orfanakis shared his homebuilt optical CT scanner, for which he won the 1st prize in Science on Stage Europe 2017! Read the comments below for full documentation on his build.

Resources on optical CT:

The history and principles of optical computed tomography for scanning 3-D radiation dosimeters by S J Doran and N Krstaji

Three-dimensional image reconstruction for CCDcamera based Optical Computed Tomography Scanner by Hannah Mary Thomas T, Student Member, IEEE, D Devakumar, Paul B Ravindran

Focusing optics of a parallel beam CCD optical tomography apparatus for 3D radiation gel dosimetry by Nikola Krstaji´c and Simon J Doran

Step 1: Computed Tomography and Photogrammetry Background

CT scanning requires a source of radiation (e.g. x-rays or light) on one side of an object and detectors on the other side. The amount of radiation that makes it to the detector depends on how absorptive the object is at a particular location. A single image acquired with this setup alone is what produces an X-ray. An X-ray is like a shadow, and has all the 3D information projected into a single 2D image. To make 3D reconstructions, a CT scanner acquires X-ray scans over many angles by either rotating the object or the source-detector array.

The images collected by a CT scanner are called sinograms, and they display absorption of X-rays through one slice of the body vs. angle. Using this data, a cross section of the object can be acquired by using a mathematical operation called the inverse Radon transform. For full details on how this operation works, check out this video.

The same principle is applied for the optical CT scanner with a camera acting as the detector and the LED array acting as the source. One of the important parts of the design is that the light rays that are collected by the lens are parallel when travelling through the object. In other words, the lens should be telecentric.

Photogrammetry requires the object to be illuminated from the front. Light is reflected off the object and is collected by the camera. Multiple views can be used to create a 3D mapping of the surface of an object in space.

While photogrammetry enables surface profiling of an object, CT scanning enables the reconstruction of the internal structure of objects. The major disadvantage for optical CT is that you can only use objects that are semi-transparent for the imaging (e.g. fruits, tissue paper, gummie bears, etc.), whereas photogrammetry can work for most objects. Furthermore, there is much more advanced software for photogrammetry so the reconstructions look incredible.

Step 2: System Overview

I used a Nikon D5000 with a 50mm focal length f/1.4 lens for imaging with the scanner. To achieve telecentric imaging, I used a 180mm achromatic doublet separated from the 50mm lens with a tube extender. The lens was stopped down to f/11 or f/16 to increase the depth of field.

The camera was controlled using a shutter remote that connects the camera to an Arduino Nano. The camera is mounted to a PVC structure that connects to a black box that holds the object to be scanned and electronics.

For CT scanning, the object is illuminated from the back with a high-power LED array. The amount of light collected by the camera depends on how much is absorbed by the object. For 3D scanning, the object is illuminated from the front using an addressable LED array that is controlled with the Arduino. The object is rotated using a stepper motor, which is controlled using an H-bridge (L9110) and the Arduino.

To adjust the parameters of the scan, I designed the scanner with an Lcd screen, two potentiometers, and two push buttons. The potentiometers are used to control the number of photos in the scan and the exposure time, and the push buttons function as an “enter” button and a “reset” button. The Lcd screen displays options for the scan, and then the current status of the scan once acquisition begins.

After positioning the sample for a CT or 3D scan, the scanner automatically controls the camera, LEDs, and Motor to acquire all the images. The images are then used for reconstructing a 3D model of the object using Matlab or PhotoScan.

Step 3: Supply List

Electronics:

Camera and lighting:

Light box:

  • 2x 26cmx26cm ¼ inch thick plywood
  • 2x 30cmx26cm ¼ inch thick plywood
  • 1x 30cmx25cm ½ inch thick plywood
  • 2x ½ inch diameter dowel rods
  • 8x L-shaped PVC joints ½ inch diameter
  • 8x T-shaped PVC joints ½ inch diameter
  • 1x PVC cape ½ inch diameter
  • 4feet 1x2 pine
  • Thin aluminum sheet
  • Black poster board
  • Nuts and bolts
  • Spring

Tools:

  • Soldering iron
  • Power drill
  • Wire wrap tool
  • Dremel
  • Jigsaw
  • Wire cutters
  • Scissors
  • Tape

Step 4: Box Design and 3D Mounts

I designed the camera mount and box using Fusion360. The PVC pipe portion of the design was inspired by DIY steadicam jigs that are used to stabilize cameras for video. The box had to block out light from the surroundings, and provide precise alignment of the sample and the camera. To mount several of the components, I also designed several custom parts in Fusion and 3D printed them. Here is a list of the parts that I printed.

3x Dowel rod mounts to connect the camera to the black box

2x LED module mounts to connect the LED to the black box

1x Stepper motor mount

1x Object stage that connects to motor shaft

1x Object spear that connects to motor shaft

1x Handle for black box lid

2x Cable mount for fixing the LED power cable and camera remote to the light box

Once these parts are printed, you will be able to assemble the rest of the scanner. I have provided .stl files for download in this step.

Step 5: PVC Camera Mount Assembly

The PVC joints were painted black. To achieve a homogenous black, I used about five coats of black. Try your best to not get paint in the joints.

After painting, I assembled the jig for holding the camera described in this video. A hole is drilled in the bottom of one of T-joints and PVC cap. A 2 ½ inch bolt is pushed through the T-joint A spring is placed around the bolt and two nuts are used to put the spring in slight tension.

The dowels were then cut as follows using a jigsaw and wood saw:

  • 1X 17cm
  • 2X 14cm
  • 4X 9cm
  • 8X 5.5cm
  • 4X 5cm
  • 2X 3.2cm

After cutting the dowels, they were inserted into the PVC joints. Unfortunately, they were a much tighter fit than I expected! I had to sand down the dowels and hammer them into the joints.

Step 6: Construct Light Box

Next I built up the box using plywood and 1x2 planks. The sides were nailed into the planks, and holes were cut for the camera, LED array, and front panel. After the box was assembled, the dowel rod mounts were attached to it so that they aligned with the camera mount. The LED was also mounted using the 3D printed mounts.

To power the LED, I connected a 2.1mm x 5.5mm barrel plug into the back and ran the cable into the box. The cable was held in place using 3D printed plugs. In addition to the plug for the LED power, the remote cable also must go through the box to connect the camera trigger to the prototype board.

Finally, I created a lid for the box. The 3D printed handle was attached using two bolts.

Step 7: Camera Setup and Triggering With Arduino

Because 3D and CT scanning requires many images, automating the shutter of the camera is beneficial. For a full range of ways to do this check out this instructable by Jason Poel Smith. I decided to trigger the camera using a remote shutter and the arduino in the scanner. Cut the remote shutter cable. The wires are labeled as follows:

Yellow – focus

Red – shutter

White – ground

In order to focus the shot, the yellow wire must be connected to ground. To snap a photo, both the yellow and red wire must be connected to ground. I connected a diode and the red cable to pin 12, and then I connected another diode and the yellow cable to pin 13. The diodes protect the camera from any signals sent from the Arduino, as suggested by Jason. When a photo needs to be taken, both pins 12 and 13 are grounded. Otherwise, the pins are set to HIGH. If you don’t need to focus and snap photos separately, I think you could connect both the yellow and red cables to the same pin.

I was really stumped on using the shutter remote because I didn’t realize that there is directionality to the jack! Make sure that you have the jack inserted correctly into the camera as indicated by the arrows on the camera and jack.

Step 8: Solder Board for System

With the box assembled, I soldered the arduino, Hbridge, Buck converter, potentiometer for the lcd screen, and resistors to a prototype board. The power supply is 12V, so to power the arduino, motor, and addressable LEDs I used a Buck converter to convert the 12V to 5V. I then checked the stepper to make sure that it worked. Here is how it should be connected to the H-bridge:

  • OA1 - Blue
  • OB1 - Red
  • OA2 - Green
  • OB2 - Black

I had some issues powering the motor with the buck converter. It would randomly start moving. After troubleshooting, I connected it to the Arduino 3.3V pin with a diode so that the motor current didn't drag the 5V down.

Step 9: Making the Front Panel

I wanted to try something new with the front panel, so I tried printing the panel design onto a sheet of aluminum. I followed this video by DeltaGeek. The panel design is printed backwards with a laser jet printer. Place the sheet of paper onto the aluminum panel and iron it for 10 minutes. Then soak the panel in cold water. This technique worked pretty well after trying only a few times on test aluminum. Make sure not to have the steam on for the iron!

I then drilled out holes with a drill press or dremel and attached the switches, potentiometers, power switch, usb extension cable, and power jack to the panel. Cables were soldered on before placing it into the box.

Step 10: Mounting the Panel, Motor, and Addressable LEDs

The prototype board was connected to the 3D printed mount using PCB standoffs. Then it was screwed to the bottom of the light tight box. I attached the front panel to the box and connected its components to the appropriate nodes on the prototype panel.

The motor was then screwed into the bottom panel next to the electronics and connected to the H-bridge. It is crucial that you align the motor mount with the camera lens! Otherwise, the CT constructions will be distorted.

I soldered the addressable LED strip to be placed on the wall where the lens enters the box. Initially, I attached the LEDs directly to the wood. However, after some poor scans, I decided to add black poster board to eliminate scattered light.

Step 11: Acquiring Data

The hardware for the scanner is complete! I wrote the code so the lcd screen tells the user how to run the scan. You can pick either a photogrammetry scan or a CT scan, the number of images, and exposure time of the camera. I designed two stages for the scanner: one flat table and one with a nail that can pierce soft objects for CT scanning.

The object is illuminated from the back for CT scans and from the front for surface profile scans (photogrammetry). The angle the object is rotated is equal to approximately 360degrees divided by the number of images to be acquired. For this stepper motor, there are 200 turn per revolution so the number of images acquired must be a multiple of 200. The code is written to rotate the object, pause, and snap a photo with the camera.

Once the scan is complete, the images from the SD need to be uploaded to a computer for constructing a 3D model.

Libraries required:

Step 12: Reconstruction and Results

To see all the results from the scanner, check out my website.

CT scans:

The images for the CT scan were uploaded into Matlab, and then the images are reshaped to form sinograms. Each column in the image forms a sinogram. One of the gif above shows the sinograms for all the columns. A single sinogram creates a cross section in the image by using the inverse Radon transform.

The two other gifs play one cross section of a tomato and lemon slice at a time. You can see seeds entering and leaving the cross section demonstrating that the reconstruction successfully identified seeds at different depths in the tomato. An entire 3D object is formed by stitching the cross sections together.

I have attached the Matlab code for now. I'm planning to write Python code for doing the CT reconstructions too.

Photogrammetry:

I used Photoscan on my Mac for processing the images for 3D scanning. The results were incredible! Even with the white background provided with the light box, it takes a lot of time cropping images. I am working on writing code for improving the cropping. To learn how to use Photoscan, I follow this video tutorial. The images are cropped and points are identified for the surface profile. You can see the camera positions predicted by the software, which should be in a perfect circle around the object. A sparse point cloud is created first, followed by a dense cloud, mesh, and texture.

Results:

Overall, I have been happy with the results from the scanner. PhotoScan is impressive software that does most of the work for creating incredible 3D models. I have some gaps in the photogrammetry results due to the camera being only at one elevation. For CT scanning, there were much fewer objects to scan, but I was still happy everything worked. In comparison to photogrammetry, CT scanning makes constructions of what is inside objects (even though it only works for transparent objects). Because I wrote the code, I feel I have a much better idea how the reconstruction works.

And that’s the project. Thanks for reading the instructable!

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    We have a be nice policy.
    Please be positive and constructive.

    Tips

    3 Questions

    Hi,

    Great project!

    Just wondering where I can find the stl files for the 3D mounts?

    Thanks,

    Steph :)

    Thanks! Looks like I forgot to add STL files. Just added it to Step 4.

    Could I use a different camera for this. I have an old Digital Rebel. It is 5Meg I think

    Yes, a different camera will work. Michalis made his optical CT scanner with a webcam. See the comments below. Best of luck with the build!

    0

    "I have attached the Matlab code for now. I'm planning to write Python code for doing the CT reconstructions too."

    i can't find the Matlab code.

    Help, please

    thanks you

    Hello, it is at the bottom of Step 12.

    55 Comments

    This is an amazing project! Well explained and using various technics with PVC, wood, 3D printing, Arduino, and photogrammetry. Thanks for sharing!

    2 replies

    Thanks for checking it out, Matlek!

    And congrats for the Grand Prize!

    Awesome! Got to try this sometime, maybe with a Raspberry Pi...
    By the way, what do you think about using sound instead of light?

    1 reply

    Thanks for checking it out! RaviG28 suggested using a Pi too. You could display the images in real time and even do the processing automatically on the Pi right after scanning.

    Using sound is definitely feasible. There is a technique called Photoacoustic Tomography that uses light to excite the sample and detects ultrasonic waves emitted. You could also set up ultrasonic sensors and do 3D scanning, similar to what Super Make Something does with IR sensors: https://www.youtube.com/watch?v=-qeD2__yK4c

    Wow! That's great! Congratulations! :D

    1 reply

    very impressive been trying to figure out a way to scan small objects for model making and found this. it is perfect for my needs. only question is the distance between the lens and the object is this critical, and is the camera set for macro photography.

    There is one change that I will do and that is make it so the camera will pivot vertically around the centre of the object so I can see the top and bottom of the model. While mounting it on a fine stick

    1 reply

    The distance shouldn't matter when using a telecentric lens. However, there may be some weird magnification issues when imaging too closely to the object. Here is a link for some advice on imaging small objects with photogrammetry: https://www.reddit.com/r/photogrammetry/comments/4n03js/tips_on_small_objects/

    Good idea with image from multiple heights to get better coverage of the object.

    Best of luck with the project!

    Great Job my friend! I am a Science teacher and last year I built two optical CT Scanners one with LEGO Mindstorms and one with Arduino and it gave me the 1st Prize in National Science on Stage 2016 and the 1st prize in Science on Stage Europe 2017 (32 countries, 450 Science teachers). Science on Stage is the biggest competition for Science Teachers worldwide. Check this video:

    you can find all the material (instructions, image sets, code etc) here:

    https://goo.gl/Mffb1m

    I use my systems in school to present tomography principles and CT Scan fruits, gummy bears etc.

    The main differences with your system is that I used a usb web cam and imageJ for the 3D reconstructions. I also used MATLAB to control Arduino and LEGO EV3 for image acquisition and for implementing radon transforms.

    I am very happy that you did something similar with great design and I pretty much know how much time you spent for this work...

    Voted for you!

    Cheers

    Michalis

    3 replies

    Hi Michalis,

    Thank you for sharing your optical CT scanner project and all of your documentation. And congratulations on winning those competitions too! This is a perfect project to get students interested in imaging.

    Your implementation, write-up, and results are terrific. I especially love your idea to use two polarizers to ensure that only light scattered in the specimen makes it to the camera. I guess that my results worked out okay because the rays of light from the source saturated the sensor if they did not travel through the sample. You also initially had some issues with scattered light in the box, which implies that using black out paper on the walls is really crucial for these homebuilt optical CT machines.

    I am also happy to see that this setup works using a webcam instead of a much more expensive dSLR. I downsample the images anyway for my reconstruction. Did you add any lenses in front of your webcam? If not, I wonder how big of a difference the telecentric lens that I used makes for the CT imaging.

    The last major thing that I might not have emphasized enough in this write-up was the importance of making sure that the axis of rotation is vertical and directly in the middle of the image. I actually just eyeballed the center of the images when cropping afterwards. I guess it was good enough for most scans, but I am now going to adjust my code to make sure that the axis is right in the middle of the image.

    Great results with the gummie bear reconstruction. I am impressed how clearly you can see the hole in the bottom where you mounted the sample.

    Thanks for voting!

    Hi jbumstead,

    Thank you for your kind words, The trick with the linear polarizers is common in biomedical imaging and this project was the simplified transformation of a scientific experiment to secondary education. Initially without the polarizers I had the same issues as you of course so try the trick it will make a difference in your results.

    I think the most crucial factor is to have a perfect vertical axis in the middle in your images otherwise the iradon function of MATLAB will give you distorted CT Scans. I crop the images within the MATLAB code to center them and get rid of unwanted parts of the image and then the code produces a 3D matrix .tiff file with all the CT Scans of the object.

    Then I use the open source ImageJ Fiji software which is specialised for biomedical imaging and which is used by scientists worldwide so as to get the 3D reconstruction with a few clicks.

    Once I have used a webcam with x10 lens with simiral result. My intention as an upgrade was to use a DSLR camera but initially I wanted to develop the most simple and inexpensive ct scanner and showcase that it can be used in secondary education. the arduino ct scanner costs below 100euro.

    I have made several experiments with different objects, sweets, fruits, plants even insects... objects with a lot of sugar insider are the best light scatters and give better results

    Looking forward to see more of your work and wishing you all the best and success in the contest!

    Best regards

    Michalis

    Hi Michalis,

    I will have to try the linear polarizers and ImageJ for making the 3D reconstructions. I have already updated my matlab code to make sure the axis of rotation is directly in the center of the image.

    Excellent work keeping costs below 100euro. The dSLR will definitely help with resolution, easy triggering, and adjustable exposure. Right now I downsample the image so that it doesn't take so long for the reconstructions. The amount I downsample depends on how much I crop the image (e.g. how big the object is) and how long I want to wait.

    Lots of sugar is good. Maybe this is why Jaswant suggested soaking in saturated sugar solution.

    Wow, amazing project! Congratulations!

    Awesome Project , I'm now planning on building one similar , when it came to the software did you use the standard version of Photoscan or the Professional ? I'm hoping the Standard will work cant figuire dropping $3k on a project. Thank You !!

    1 reply

    I was able to make 3D scans with the demo version, which is standard Photoscan. However, I couldn't export files, so I downloaded the free trial, which is the professional version. If you buy the standard version, you can of course export files too. For a beginner with this software, I couldn't tell much of a difference between standard and pro.

    I used Photoscan because I have a Mac, but there are other options. The free instructables class uses Recap Photo, but it requires windows so you will need to run parallels on your mac. You get it for free if you have a .edu email account. I would have used Recap Photo, if there was a Mac version.

    Mi_Tasol also suggested trying a program called Irfanview, but I haven't tried it yet. https://www.irfanview.com/