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Chuk Goodin
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Chuk Goodin

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Seeing #RoyalBlood  on Sunday, should be good!
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Oops, it was Saturday. But it was excellent!
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At Capilano University today for a conference. Seems a little more rural than Simon Fraser University. 
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Yesterday's commute #sky
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Beautiful
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54-40 tonight -- their 50th show at the Commodore Ballroom.

54-40 I Go Blind

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Good show -- and the band bought everyone in the audience a free drink, and I found $5 on the floor at the end of the show. 
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Dandy Warhols at the #Phoenix Concert Theatre in Toronto on June 5th, 2013 #dandywarhols
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Chuk Goodin

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#TBT to when a future Prime Minister saved the life of a former PM/current Head of the Opposition
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http://www.nealstephenson.com/seveneves.html

The release of a new Stephenson novel should be a statutory holiday.
The personal website of author Neal Stephenson, unless it's been hacked.
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Sweeet
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#FranzFerdinand 4 drummers, no waiting
Double header after #BombayBicycleClub the night before!
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Happy Star Wars Holiday Special anniversary everyone!
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Medical visualization, it's what I see and do
I was going to summarize an article about the history of medical visualization that was discussed in MIT Technology Review in 2012.
The Future of Medical Visualisation
http://goo.gl/HnpAQq
However, I think that the #OpenAccess  article that they reference does a good job on its own. It's kind of strange to think of a review of a review of a review article.
From individual to population: Challenges in Medical Visualization
http://arxiv.org/pdf/1206.1148v2

Rather than review the review of the review, I'll add a few comments and answer your questions. So read either the MIT Tech Rev article or the journal article and ask questions. This is an opportunity to talk to a scientist that works in the medical imaging field.

The article mentions multi-modal volume visualization. If you have been following my  #CHMedicalImagingSeries then you know that each imaging technique (modality) has strengths and weaknesses. Combining imaging modalities, like the MRI and CT below of my head, allow you to take advantages of the strengths and minimize the weaknesses. To get the best out of multi-modality imaging you need to be able to fuse the images. The technical term is image registration or some like image co-registration. There is a lot of research in just this technique to make it more automated. One common technique is called mutual information. Our brains can easily tell that the dark material in MRI is bone (e.g. my skull) and it should match the bright material in CT. Mutual information tells the computer to consider that bright could equal dark by normalizing the images first. The principal axes of the objects are also used to register (align/fuse) the two images. For therapy planning, both surgery (cosmetic) and tumor resection/radiation, multi-modality imaging can have a huge benefit. They mention that in 1993 Altobelli used multi-modality imaging to visualize the possible outcome of complicated craniofacial surgery.

Another use of medical imaging visualization is virtual colonoscopy. Visualization tools that you need are surface/volume rendering, skeletonization, and segmentation.
UCSF Radiology: What Virtual Colonoscopy CT Scans Look Like

Surface/volume rendering is just what it sounds like. The data is analyzed and the surface can be identified and displayed with shading and lighting such that it looks 3D. You can make it true 3D with the right equipment (3D glasses, 3D monitor, and software to split the data into left and right views) but that's not essential. It can't be emphasized enough that modern GPUs have made these difficult calculations become trivial. Some of the early animation work and medical image visualization required high end UNIX workstations. Now that same level of visualization can be done with a low-end gaming PC.

Segmentation is also, just as it sounds. There are automated and manual segmentation tools. For example in the heart and skeleton images below, the tissue of interest has been segmented out of the "background" tissue, e.g., the internal organs, muscle, etc. Again, there is research in this technique alone. Our brain can look at a medical image and identify parts of the brain or organs quickly. "Teaching" a computer program to do that automagically is very difficult, especially if there is motion due to breathing. In that case, you may have to use image registration to get rid of the motion blurring first.

Skeletonization is a process of identifying paths. For colonoscopy, that would be teaching the program to traverse the path of the colon. I've done work where we were measuring blood vessel diameters in a pulmonary hypertension model. Skeletonization was used to automatically identify each part of the vascular tree. From there, it was easy for the software to measure each diameter.

The first three images are fused images of a CT and MRI of me. The yellow surface rendered part is from CT as it shows bone (skull) very well. The grey-scale part of the image is MRI which shows soft tissue very well. The rest of the images are from a Toshiba 320 slice CT. In CT technology, a ring of detectors is used capture the signal from the x-ray source. Each ring is called a slice in clinical CT machines. For a while 64 slice was considered the best. Now 256 and 320 slice machines are becoming available. More slices means you can cover a larger area in a shorter amount of time. So highly detailed images of the heart can be acquired without motion artifacts from the beating heart. Likewise for the lungs.

Here's a few older posts that will hopefully help you understand the article.

Medical Imaging 101 pt 1 (http://goo.gl/LTWUf)
Medical Imaging 101 pt 2: CT (http://goo.gl/IHaFw)
Medical Imaging 101 pt 3: MRI (http://goo.gl/UVbiU)
Functional vs. anatomic image (http://goo.gl/UTPK7)
Visible Human project (http://goo.gl/cv2xU)
Eye of Horus post (http://goo.gl/qpxyh)

Image sources other than the above article:
Lung and brain CT images (http://goo.gl/HHhqSJ)

CT Heart (http://goo.gl/eqbFde)
#ScienceSunday  
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Spiderling swarm.
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