# Conventional and Deep Learning Methods for Skull Stripping in Brain MRI
## 3 Classical or Conventional Skull Stripping Approaches  
### Histogram Thresholding with Mathematical Morphology  
Thresholding with mathematical morphology-based algorithms utilizes thresholding using histogram analysis, edge detection, and a series of morphological operations--erosion, dilation, opening, closing, etc.--to isolate the brain and the non-brain regions. For instance, one of the most commonly used methods based on this technique was made by [PERSON] et al. [43]. It discriminates the skull from the brain by exploiting histogram thresholding followed by mathematical morphology filters. [PERSON] et al. [44] developed a multistage approach that utilizes anisotropic filters, histogram thresholding, a morphology filter, and snakes contouring techniques for segmenting the brain. [PERSON] et al. [45] presented a similar histogram-based brain segmentation (HBRS) method based on \begin{table}
\begin{tabular}{c c c} \hline \hline
**Dataset Name** & **Comments** & **Link** \\ \hline BrainWeb & BrainWeb simulator & [[http://www.bic.mni.mcgill.ca/brainweb/](http://www.bic.mni.mcgill.ca/brainweb/)]([http://www.bic.mni.mcgill.ca/brainweb/](http://www.bic.mni.mcgill.ca/brainweb/)) \\ IBSRI-2 & 20 and 18 T\({}_{1}\)W MRI & [[http://www.cma.mgh.harvard.edu/lbs/](http://www.cma.mgh.harvard.edu/lbs/)]([http://www.cma.mgh.harvard.edu/lbs/](http://www.cma.mgh.harvard.edu/lbs/)) \\ Volume & & [[http://mrbrains13.isi.uu.nl/](http://mrbrains13.isi.uu.nl/)]([http://mrbrains13.isi.uu.nl/](http://mrbrains13.isi.uu.nl/)) \\ MRBrainS-5 & 5 T\({}_{1}\)W and T\({}_{2}\)W FLAIR & [[http://mrbrains13.isi.uu.nl/](http://mrbrains13.isi.uu.nl/)]([http://mrbrains13.isi.uu.nl/](http://mrbrains13.isi.uu.nl/)) \\ SVE & 40 T\({}_{1}\)W & [[https://www.nitrc.org/projects/sve/](https://www.nitrc.org/projects/sve/)]([https://www.nitrc.org/projects/sve/](https://www.nitrc.org/projects/sve/)) \\ ADNI & T\({}_{1}\)W and T\({}_{2}\)W & [[http://adni.loni.usc.edu/data-samples/access-data/](http://adni.loni.usc.edu/data-samples/access-data/)]([http://adni.loni.usc.edu/data-samples/access-data/](http://adni.loni.usc.edu/data-samples/access-data/)) \\  & 2000 T\({}_{1}\)W, T\({}_{2}\)W, FLAIR, & \\ Oasis & ASI, SWI, time of flight, & \\  & resting-state BOLD, and & \\  & DTI sequences (Oasis3) & \\ LPBA40 & 56 MRI images & [[https://resource.loni.usc.edu/resources/atlases-downloads/](https://resource.loni.usc.edu/resources/atlases-downloads/)]([https://resource.loni.usc.edu/resources/atlases-downloads/](https://resource.loni.usc.edu/resources/atlases-downloads/)) \\ IBSR & 18 subjects & [[https://www.nitrc.org/projects/lbsr/](https://www.nitrc.org/projects/lbsr/)]([https://www.nitrc.org/projects/lbsr/](https://www.nitrc.org/projects/lbsr/)) \\ MRBrainS13 & 20 subjects & [[https://mrbrains13.isi.uu.nl/](https://mrbrains13.isi.uu.nl/)]([https://mrbrains13.isi.uu.nl/](https://mrbrains13.isi.uu.nl/)) \\ NAMIC & 40 T\({}_{2}\)W & [[https://www.insight-journal.org/midas/collection/view/34](https://www.insight-journal.org/midas/collection/view/34)]([https://www.insight-journal.org/midas/collection/view/34](https://www.insight-journal.org/midas/collection/view/34)) \\ NFBS & 125 MRI images & [[http://preprocessed-connectomes-project.org/NFB_skullstripped/](http://preprocessed-connectomes-project.org/NFB_skullstripped/)]([http://preprocessed-connectomes-project.org/NFB_skullstripped/](http://preprocessed-connectomes-project.org/NFB_skullstripped/)) \\ CC-12 & 12 MRI images & [[https://sites.google.com/view/calgary-campinas-dataset/home/](https://sites.google.com/view/calgary-campinas-dataset/home/)]([https://sites.google.com/view/calgary-campinas-dataset/home/](https://sites.google.com/view/calgary-campinas-dataset/home/)) \\ download & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of publicly available datasets.