Lending you a hand with impage processing – introduction to ImageJ

In a previous post I used an x-ray of my left hand to showcase some basic image visualization techniques in Matlab.

If you are interested in learning image processing and analysis on your own (just like I did) but are not too interested in the programming side of things or would rather find a noncommercial alternative I’d recommend ImageJ. I just stumbled into it a few weeks ago and was immediately drawn to it.

ImageJ is a completely free, open source, Java-based image processing environment. It allows users to display, edit, analyze, process, and filter images, and its capabilities are greatly increased by hundreds of plugins on the official webpage and elsewhere.

It is used extensively by biomedical and medical image processing professionals (check this fantastic tutorial by the Montpellier RIO imaging lab), but is popular in many fields, from A-stronomy (you can read a brief review in here) to Z-oology (check this site).

I decided to give it a try right away. Within an hour of installing it on my iMac I had added the Interactive 3D SurfacePlot plugin, loaded the hand x-ray image, displayed it and adjusted the z scale, smoothing, lighting, and intensity thresholds to what (preliminarily) seemed optimal.

For each discrete adjustment I saved a screen capture, then I reimported as an image sequence in ImageJ and easily saved the sequence as an AVI movie, which is here below. I’m hoping this will give you a sense of how I iteratively converged to a good result.

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Lending you a hand with image processing – basic techniques 2

In my last post I illustrated some simple techniques to enhance and visualize a hand x-ray image. I showed how to use intensity values as if they were elevation to display the hand in pseudo-relief. I did this in 2 ways using the Matlab command surf: once keeping the elevation range of [0-255] obtained from intensity, and a second time creating a different elevation range (through trial and error) to try to further enhance the relief effect. In the case of the hand x-ray the relief was indeed enhanced but with that also unimportant details that are distracting possibly from the task (for the hypothetical specialist commissioning our image enhancement work) of interpreting the x-ray. Today I want to show you a case in which it would be useful to enhance dramatically the smaller details in an image. Below is a beautiful coin of the Roman Emperor Augustus I found here.

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Lending you a hand with image processing – basic techniques 1


This is a PA ulnar deviation x-ray of my left wrist from last month, which gives a good view of the scaphoid bone from above.

The bone is chipped in the area pointed by the arrow, due to a fall that occurred 20 or so years ago. Somewhere in there, there’s also a tiny detached fragment of cartilage that calcified (as seen in a CT scan at the time). I was lucky, because typically the result of a fall with outstretched hand for people aged 17-40 is the scaphoid fracture, which are known to have unpredictable healing. Lately, however, due to a tendonitis, the fragment too is acting out. I’m left handed so this is causing some trouble, and that’s why the recent x-rays.

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