Introducing the Dental Microwear Image Library

Dental microwear, seen in the tiny pits and scratches on a tooth, provides lots of detailed data for inferring diet and chewing behavior in animals. Analyses are often conducted by digitizing highly magnified images of the tooth surface and counting up and classifying the various microscopic features. Animals with a certain percentage of pits and scratches may have browsing habits, whereas those with another profile may be grazers. By measuring extant animals with known diet, we can (hopefully) infer the diet of extinct animals.

Dental microwear; modified from figure 3 in Mihlbachler et al., 2012

In this age of increasingly open science, microwear studies can be problematic. A cornerstone of science is reproducibility - yet, inter-observer variation and error can greatly affect measured data. Furthermore, one study alone may generate dozens or hundreds of images. Even if you wanted to re-analyze teeth, it's pretty tough - how could you get access to the necessary images? Ideally, we want a world where anyone can access the raw image data, make their own observations, double-check published analyses, and add new data for comparison.

Thus, a new project - called the Dental Microwear Image Library, or DMIL - may change things. Assembled by Brian Lee Beatty and Matthew Mihlbachler, the website aims to become a clearinghouse for dental microwear images. This will allow greater standardization of analyses and hopefully better interpretations of paleoecology and diet for extinct organisms and modern organisms. The first data (from a recent paper in Paleontologia Electronica) are now posted, along with many other data sets.

Brian Lee Beatty (who blogs at The Aquatic Amniote and tweets as @Vanderhoofius) was kind enough to answer a few questions about the DMIL. Thanks, Brian!

Was there a particular moment or incident that inspired you to build the DMIL? If so, what was it?
As we set out to test and develop the method that Nikos Solounias and Gina Semprebon started, we found ourselves frustrated by not only the lack of information on methods that were given in most microwear papers, but also the inability for people to check their work. Interobserver error is a major cause of problems for microwear, and the only way for anyone to be aware of those differences is if they compare interpretations of microwear surfaces, not just their numbers on a spreadsheet. The DMIL was the only possible solution to the need to share such images.

How has community response been so far? Is there any particular type of skepticism that you're working to overcome?
The DMIL hasn't yet come up against skepticism, but our first paper on this method that uses it has.

What license, if any, are the data housed under? Or is it on a case-by-case basis?
There is no license for the data. We want it to be completely open-access and simply available.

How would you envision the DMIL 10 years from now? What goals might you have for the long-term?
We hope it will be a place that people can use to learn how to use the methods we are continuing to develop. I most sincerely hope that it will not only be home to our own data, but also be a place for others to deposit their data using similar methods so that more work of this sort is available in a similar, comparable format.

Authors of the recent paper in PE, along with a research assistant. Photos courtesy of Brian Lee Beatty.

For more information, check out the DMIL, or read the recent paper (open access) about the work.

Citation:
Mihlbachler, Matthew C., Beatty, Brian L., Caldera-Siu, Angela, Chan, Doris, and Lee, Richard, 2012. Error rates and observer bias in dental microwear analysis using light microscopy. Palaeontologia Electronica Vol. 15, Issue 1;12A,22p.

Lizard Skulls! (the update)

In a previous post, I noted a really nifty collection of digital lizard skulls available thanks to the efforts of Nick Gardner, writer of "why I hate theropods" and a student in the Casey Holliday lab. Well, it turns out that I jumped the gun just a little bit (thanks for nothing, Facebook!). . .the complete director's cut of the page is now available, and is highlighted in a posting here. Congratulations on a really great resource!

Lizard Skulls!

Casey Holliday, a paleontologist and functional morphologist out at Marshall University, and Nick Gardner, an undergraduate at Marshall and owner of "why I hate theropods" (possibly my favorite title for a paleontology blog ever), have started posting a collection of virtual skulls.

These guys did a whole bunch of reconstructions of lizard skulls from CT scan data, and the recons are downloadable as 3D PDFs or VRML files. Check it out - it's a great way to get an appreciation for the diversity of cranial form in this group! And, look for more to come in the future.

Marshall University also has a nice article on the project.

Note: Keep an eye on Nick's blog in the coming days for more on the project.

Image Your World With ImageJ

ImageJ is probably one of the most universally-useful, open source programs available for scientists. This is a program designed for image analysis, whether you want to count points, generate an "x-ray" image from CT scan data, calculate moments of area, or measure the length and area of a feature on a photograph.

The "J" in ImageJ stands for "Java" - that platform-independent programming language. This means that you can run ImageJ on virtually any operating system. If you don't have a Java virtual machine installed (and most every system comes with one - if you don't have it, you'll find out when you can't run ImageJ!), the program's website allows you to download a copy with your installation of ImageJ. The only potential downside of running under Java is a small sacrifice in program performance in some situations.

Why Use ImageJ?
The real power of ImageJ lies in its extendability and its updatability. Updates are released for the program every week or two - these usually aren't just bug fixes, but real interface and functional improvements. Furthermore, there are scads of plug-ins and macros available. Want to import DICOM stacks more efficiently? Use a plug-in! Want to measure second moments of area? There's a macro for that! Can't find a macro to do what you want? Write one of your own!

I use two main features in ImageJ: the measurement tools and the stack tools. The measurement tools allow me to measure distances, areas, and other parameters, and I can calibrate these using a scale bar from within the photo. The stack tools are also quite handy for working with CT scan data. I use them to reslice my images in various orientations (say I have a coronal series, and want to look at another view) or to generate quick 3D volume renderings. Other programs (e.g., 3D Slicer) are better for dedicated CT work, but ImageJ is fantastic for quick-and-dirty CT data manipulation. Furthermore, the interface is simple and relatively easy to navigate.

Commercial Alternatives
Probably the closest commercial equivalent to ImageJ is SigmaScan. I used this program a few years back, so I can make at least a superficial comparison. As far as I can tell, the primary benefit of SigmaScan over ImageJ is that the former allows you to save the tracings you've made for area measurements (at least, this is a feature I found handy). A dedicated user would know other unique features, but then again ImageJ doesn't cost nearly $1,000 on academic discount.

Minor Drawbacks
There are a few limitations to ImageJ of which users should be aware. If you're going to deal with large stacks of images (such as a CT scan), you may bump up against problems in the default memory configuration for the program. Fortunately, this is usually resolved by a simple tweak of the initialization file. Also, it is important to remember that ImageJ is for image analysis, not image editing. A few tools within ImageJ (paintbrush, paint bucket, etc.) can help in this regard, but you're really better off going to GIMP for most image editing tasks. And, as mentioned above, you can't directly save and reload any selection boundaries that you might make for measuring area (if you want to remeasure the same area later).

The Bottom Line
All in all, if you measure images or work with CT slices, you want ImageJ on your computer.

Note: I forgot to mention in my initial post two other popular options - NIH Image and Scion Image, available for Mac and Windows, respectively. They have both largely been superseded by ImageJ (and were really precursors to it), but I just want to be complete.

GIMP

No, this is not an unfortunate slur - it's actually an acronym for "GNU Image Manipulation Program."* And what a program it is! GIMP is one of the most mature and functional open source programs out there, and should be the first choice for anyone looking to do any sort of image editing.

GIMP is available for Windows, the Mac OS, and Linux. The closest commercial equivalent to GIMP is Adobe Photoshop - just like Photoshop, GIMP excels at editing raster images. It is under very active development, and new versions and bug fixes are constantly on their way.

As a tool for editing photographs destined for publications or presentations, you really can't beat GIMP. It has a whole host of very functional tools for selection, touch-up, and flat-out manipulation of images. Want to rotate a portion of the image? Easy enough. Need to remove a black background and replace it with white? No problem. There's not much more I can say - GIMP is fantastic! To be perfectly honest, I haven't missed Photoshop at all since making the switch (although I am sure Photoshop "power users" might disagree).

So are there any downsides to GIMP? Some users may report slow speeds, but this seems to be largely fixed in the more recent versions. For folks who may want to do extremely hard-core editing of color images for later printing, GIMP only supports RGB color formatting (although you can choose colors on the palette using CMYK standards). This may pose a problem if you want to send your files to a professional printer, but it should not affect the average user (or the paleontologist who is usually working in grayscale images). Finally, the GIMP toolbar and image editing pane open as two separate and discrete windows, rather than as subwindows within a main window (as in versions of Photoshop that I've used). This sometimes creates a cluttered editing experience, but it's more an annoyance than anything. Integration with a tablet can be a little bit of a hassle, but it works pretty flawlessly once you get it running (and I've never tried the same task in Photoshop, so I don't know how it compares in that regard).

*GNU = a type of open source software license; it has nothing to do with the African savannah.