Review of brain MRI image segmentation methods

494 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Multivariate Mixture Model for Myocardial Segmentation Combining Multi-Source Images (2016, methodology): “the MvMM to the task of brain MR segmentation [38].”
A survey of GPU-based medical image computing techniques. (2012, background): “…an important role in practical clinical applications and acts as a preliminary stage in various diagnosis techniques, the corresponding high segmentation performance of brain MRI images is essential and crucial to provide correct diagnosis reference information for researchers and physicians (147).”
An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data (2011, background): “The chronology of progress in segmentation may be tracked through both technical reviews (Bezdek et al. 1993; Pal and Pal 1993; Clarke et al. 1995; Pham et al. 2000; Viergever et al. 2001; Suri et al. 2002; Duncan et al. 2004; Balafar et al. 2010) and evaluation studies (e.”
State-of-the-Art Methods for Brain Tissue Segmentation: A Review (2017, unknown): “the piecewise smooth case [40].”