## Spherical Brain Mapping

The **Spherical Brain Mapping** (SBM) is a feature extraction and visualization framework intended to map the internal structures and features of the brain onto a 2D image that summarizes all this information.

### Insight

Visualize 3D medical image volumes in 2D maps that highlight the statistical and textural properties of any tissue.

### Analysis

Use the statistical radial imaging biomarkers to analyze population differences.

### Labelling

Compute statistical tests on SBM maps and superimpose a template to locate significant brain regions.

### Prediction

Train and test a classifier with SBM maps to avoid the small sample size problem.

SBM allows three-to-two dimension mapping by means of some statistical measures. The system is based on a conversion from 3D spherical to 2D rectangular coordinates. For each spherical coordinate pair (θ,φ), a vector **v**(θ,φ) oriented in that direction and starting at the defined origin (usually the *Anterior Commisure*), is defined. This vector creates a set of voxels V(θ,φ) that contains the intensities of all voxels crossed by **v**(θ,φ).

From V(θ,φ), a number of **SBM measures** can be computed, including including statistical values (average, entropy, kurtosis) and morphological values (tissue thickness, distance to the central point, number of non-zero blocks). These values conform a two-dimensional image that can be computationally and visually analysed.

A number of publications have already explored the ability of SBM in the diagnosis of Alzheimer's Disease:

- F.J. Martinez-Murcia et al.
*Assessing Mild Cognitive Impairment Progression using a Spherical Brain Mapping of Magnetic Resonance Imaging*.**Journal of Alzheimer's Disease**(Pre-print). 2018. DOI: 10.3233/JAD-170403 - F.J. Martinez-Murcia et al.
*A Spherical Brain Mapping of MR images for the detection of Alzheimer's Disease*.**Current Alzheimer Research**13(5):575-88. 2016. - F.J. Martinez-Murcia et al.
*A Structural Parametrization of the Brain Using Hidden Markov Models-Based Paths in Alzheimer's Disease*.**International Journal of Neural Systems**26(6) 1650024. 2016.

### Images Gallery: No images found

### Installation

mapBrain is now available via `pypi`

and can be installed directly from:

`pip install mapBrain`

Otherwise, copy the *.py files directly to the working directory, and import the library with `import mapBrain`

.

### Quickstart

The Statistical Brain Mapping is structured as a class that can be invoked from every script. The simplest approach would be using:

```
import mapBrain
import nibabel as nib
img = nib.load('MRIimage.nii')
sbm = mapBrain.SphericalBrainMapping()
map = sbm.doSBM(img.get_data(), measure='average', show=True)
```

## And it's free!

Spherical Brain Mapping follows a GNU General Public License v3.0, so the code and all its derivatives are free (as in beer and in speech).