Yearly Archives: 2016
13 NovSfN 2016 Poster
Anatomical evaluation of Colin 27 against a database of labeled brain scans Andrew Worth1, Jason Tourville2 1 Neuromorphometrics, Inc., Somerville, MA 2 Dept. of Speech, Language, and Hearing Sciences, Boston University, Boston, MA Abstract (download poster, 7.8MB) The Colin 27 average brain is a stereotaxic registration model from the Montreal Neurological Institute (see Holmes et al. 1998). This T1 […]
Read More ...15 Oct18 Years Old and Celebrating
Neuromorphometrics turned 18 this month and to celebrate, we’re giving gifts! We have some of the most comprehensively and consistently labeled neuroanatomical regions in MRI brain scans and we’ll be providing our entire manually-labeled database to two students and/or post-docs at no cost. If you have an exciting idea about how you would use our […]
Read More ...03 MayDice Similarity Coefficients (DSCs), How Good is “Good Enough”?
If you have a method for automatic segmentation (labeling anatomy) of the human brain in MRI scans, you can test it using a ground truth segmentation by calculating the Dice Similarity Coefficient (DSC). But what affects DSCs, and how do you know if a DSC value is good or bad? Some neuroanatomical regions such as ventricles are relatively easy to segment because […]
Read More ...08 MarAutomatic labeling of MR brain images: performance approaching human accuracy
C. Ledig and D. Rueckert, in Chapter 14 of this recent book, describe segmentation of MR brain images, and conclude: “The performance of current state-of-the-art techniques is starting to approach that of human observers in terms of accuracy. However, the robustness of current approaches is not yet comparable to human observers. This is especially true […]
Read More ...02 MarWhat is a probabilistic atlas good for?
This article from Science shows why a probabilistic atlas that includes left-handed individuals is important: Brain-zapping therapies might be hitting lefties on the wrong side of the head
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