Project Name: | Get ready for BRAINSABC publication |
Goal of Project
The ultimate goal is a publication of BRAINS ABC, bias field correction too, through out experimental comparison to the Atropos:
- Code revision to support for multiple images of same modality (small differences).
- Atropos running scheme
- Plan for comparison including data selection, criteria for comparison, and more.
If the script is ready, HBM conference (Abstract due is usually January) will be the target.
Current Project Status/Notes
Reading materials and running small tests to familiarize to BRAINSABC code/results.
Timeline/Milestones
- 01/27/2013 First experimental setup
- 01/31/2013 First Draft with Blank Experimental Results
- 02/01/2013 Experimental setup finish up
- 02/07/2013 Second Draft with completed method section
- 02/09/2013 First round of experimental result
- 02/13/2013 Experimental write up with draft of discussion
- 02/16/2013 Finish up add-up experiments
- 02/20/2013 First completed draft
- 02/23/2013 First review by Hans
- 02/25/2013 Second revision
- 02/28/2013 Final revision
- 03/01/2013 Submission
Jira
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Child pages
Items pending
Deliverables:
- Working code of BRAINSABC for multiple images of same modality that is really similar
- Method description of BRAINSABC
- Experimental section prooving BRAINSABC performace
- Compare Affine and Syn (Tentative)
- Compare to Atropos (Tentative)
- Publication submission to MICCAI 2013
Materials
- Avants, B. B., Tustison, N. J., Wu, J., Cook, P. a, & Gee, J. C. (2011). An open source multivariate framework for n-tissue segmentation with evaluation on public data. Neuroinformatics, 9(4), 381-400. doi:10.1007/s12021-011-9109-y
- Lorenzen, P., Prastawa, M., Davis, B., Gerig, G., Bullitt, E., & Joshi, S. (2006). Multi-modal image set registration and atlas formation. Medical image analysis, 10(3), 440-51. doi:10.1016/j.media.2005.03.002
- Prastawa, M., Bullitt, E., Moon, N., Van Leemput, K., & Gerig, G. (2003). Automatic brain tumor segmentation by subject specific modification of atlas priors1. Academic Radiology, 10(12), 1341-1348. doi:10.1016/S1076-6332(03)00506-3
- Prastawa, M., & Gilmore, J. (2004). Automatic segmentation of neonatal brain MRI. Medical Image Computing and ..., 10-17. Retrieved from http://www.springerlink.com/index/ENYFGRR6YYLFCAM6.pdf
- Prastawa, M., Gilmore, J. H., Lin, W., & Gerig, G. (2005). Automatic segmentation of MR images of the developing newborn brain. Medical image analysis, 9(5), 457-66. doi:10.1016/j.media.2005.05.007
Ultimate Project Goal
Ultimate project goal is to submission to MICCAI 2013 of as a methodology paper.