Posted By: John Muschelli - Oct 10, 2019
Tool/Resource: Non-Contrast Head CT of Stroke Patients with Brain Masks
 
We have released the data at: https://archive.data.jhu.edu/dataset.xht...
Please cite:
Muschelli, J., Ullman, N. L., Mould, W. A., Vespa, P., Hanley, D. F., & Crainiceanu, C. M. (2015). Validated automatic brain extraction of head CT images. https://doi.org/10.1016/j.neuroimage.201... Neuroimage, 114, 379-385.

and

Hanley, Daniel; Mould, Andrew; Ullman, Natalie; Muschelli, John, 2019, "Head CT Scans associated with 'Validated automatic brain extraction of head CT images'", doi.org/10.7281/T1/CZDPSX, Johns Hopkins University Data Archive, V1

when using this data

Description:
The data consists of 35 different subject's non-contrast CT scan, with 2 subjects having 2 scans but every other subject having one scan (in tarballs). One subject additionally has 2 scans, but from the same time point, but with different convolution kernels. Each scan has at least one reader's manual segmentation of the image to delineate the mask of the brain areas (including cerebrospinal fluid (CSF)). The data are from the Minimally-Invasive Surgery plus rt-PA for Intracerebral hemorrhage Evacuation (MISTIE) Phases II and III clinical trials the Clot Lysis: Evaluating Accelerated Resolution of Intraventricular Hemorrhage (CLEAR) Phase III clinical trial. Each tarball contains a series of NIfTI (Neuroimaging Informatics Technology Initiative) files. These files can be read using common tools such as ITK-SNAP (http://www.itksnap.org/pmwiki/pmwiki.php), Mango ( http://ric.uthscsa.edu/mango/), or Papaya (http://ric.uthscsa.edu/mango/papaya.html). Each image has manual segmentation from 2 different readers which is a binary image delineating the brain and an automated estimate of the brain by the method proposed in the paper below.

Please cite the originoan
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