seg_EM is a general purpose intensity based image segmentation tool. In it's simplest form, it takes in one 2D or 3D image and segments it in n classes. This function has implemented several other improvements (Please click the hyperlinks to go to specific sections):
- Input anatomical priors, either as a series of images or as a 4D image.
- These priors should be pre-registered using for example NiftyReg.
- Markov Random Field for spatial consistency
- Bias field inhomogeneity correction to compensate for B0 non-uniformities as per Van Leemput et al. TMI (1999) .
- The Bias corrected image can also be outputted
- Outlier detection as in Van Leemput et al. TMI (2001)
- Prior relaxation as in Cardoso et al. MICCAI (2011)
- Semi-conjugate prior over the model parameters as explained in Cardoso et al. MICCAI (2011)
The help for this function can be obtained by running