Showing posts with label IMAGING. Show all posts
Showing posts with label IMAGING. Show all posts

Sunday, December 27, 2009

AN IDEA TO BUILD LOW COST CAT SCANNER?-BIOMEDICAL IDEAS OF PROJECTS



[caption id="" align="aligncenter" width="300" caption="Image via Wikipedia"]A Philips 64 slice 'Brilliance' Scanner[/caption]


IDEA


CAT Scanning


I'd like to build a CAT Scanner. It turns out that the software isn't that hard. The algorithm is quite simple. Here are some sample images that illustrate the process. Since I don't yet have the hardware to generate x-ray slices of an object I have synthesized what an x-ray would yield if it scanned an object. These scans are then reassembled to yield the original target image.

In a real CAT Scan system the 1 dimensional slices would be taken from the horizontal row of a series of x-rays. In this demo I don't yet have the x-rays to work with so I synthesize the 1D bands from the target image that I want to regenerate. So given a target image I generate a series of 1D radial slices by rotating the target image and then averaging all values in the rows of the image. Then I rotate the slice back to the original angle.

Slices are synthesized from a 180 degree rotation of the target image.












Relative position of each scan slice

The target and four
1-dimensional sections.
The position of the
sections corresponds to
the angle of projection.

image:target.pngimage:section_4_0.png
image:section_4_3.pngimage:section_4_2.pngimage:section_4_1.png

Add (overlay) the four 1D radial sections together to get the CAT scan image at the right.

image:section_4_0.png+image:section_4_3.png+image:section_4_2.png+image:section_4_1.png = image:target_4_out.png

The resulting CAT scan is reminiscent of the target, but it is ambiguous. I found that you need at least 8 sections to get a recognizable image. The more sections you use the better. Here is a composite of 8 radial sections:

image:targetd_animated.gif image:target_8_out.png

And finally, here is 32 radial sections. This seems to be a good number for an image this resolution:

image:target_32_out.png

This simple algorithm will work with very complex images. Given a photograph I synthesized 32 1-dimensional scans and then regenerated the photograph using the CAT algorithm.


A more complex example


image:target_n.png image:target_n_out.png image:target_n_out_enhanced.png

The real world of x-rays is not so simple. In the experiments above, I actually synthesize the radial sections by averaging all the pixels in the rows. This roughly approximates how an x-ray reveals average density of a line through the target. But in the real world there can be materials inside the target that are so dense that they totally block x-ray energy. This reconstruction technique assumes that every part of a target is at least somewhat transparent. If there are parts of a target that are totally opaque even to x-rays then this will result in ambiguous, hidden sections. These hidden sections not only hide what is inside of them, but they also cause shadows that distort areas outside.

The following target is similar to the one used before except that it now has a screen added. The algorithm that synthesizes the radial sections was modified to treat any red are as totally opaque. The result is that anything inside the cup shaped screen is totally hidden. The dense area also throws off the contrast so that it is difficult to see the notch at the top of the target, but you can more or less make it out.

image:targeto.png image:targeto_out.png


Image processing


The image that results from the composite of the 1D sections has very low contrast. It is simple to expand the dynamic range of the image, but also note that the contrast is weighted towards the center. This is because the radial sections favor the center of the image. The center of the target has the most overlapping sections so the pixels near the center contribute more signal to the average. It's difficult to apply a uniform contrast enhancement over the entire image because the result will leave the edges too dark or the center too light. What is needed is contrast enhancement that will be weighted based on the distance from the center of the image.

THIS IDEA IS IMPLEMENTABLE ALREADY WORK IS GOING ON IT

IT IS TAKEN FROM INTERNET

FROM

WWW.NOAH.ORG



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HOW TO MAKE AN DETECTOR FOR X-RAY AND GAMMA RADIATION SOURCE?-BIOMEDICAL IMAGING PROJECTS



[caption id="" align="aligncenter" width="300" caption="Image via Wikipedia"]The danger classification sign of radioactive ...[/caption]


This describes how to build a simple detector for x-ray and gamma sources. The primary sensor is a modified photodetector. It may be built around a photodiode, phototransistor, or photodarlington. I have not tested this detector yet. An amplifier will be needed to allow measurements to be made with the detector. Unfortunately, I have been too lazy to build and test an amplifier for this. If someone wants to build me a simple amplifier that I can attach to a sensor and allow me to make measurements with a multimeter then I will send you a free sensor.

The following describes how to build the sensor. The only special component is Zinc Sulfide (ZnS) which is not too hard to order from a chemical supplier. It is fairly safe to handle.

The idea is that ZnS will glow when hit by gamma radiation. The photodector then senses this light. There are a few problems associated with this. First is calibration. How do you make quantitative measurements with this? Second is that ZnS has a long hysteresis. It will glow long after being activated by x-rays. In theory, you could calibrate the sensor and measure the decay rate of the ZnS and compensate the output based on last exposure time and known decay rate. This would require a very intelligent detector! Another possibility would be to create an array of sensors with each sensor screened by various thicknesses of lead. The relative output of the detectors should be easier to convert into a meaningful number. At this point you might as well buy a real Geiger counter or gamma ray detector.

The sensor should still be useful for qualitative x-ray detection ("Is there any radiation around here?").

1. Start with photodetector (photodiode, phototransistor, or photodarlington)



2. Coat with transparent glue



3. Dust with zinc sulfide (ZnS). Sensor is now almost ready to go.



4. Package sensor to block outside light. For example, heat shrink tubing and black electrical tape.



THIS IDEA HAS BEEN TAKEN FROM http://www.noah.org/
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