AI4M Course 1 week 3 lecture notebook
Explore the data
In this week's assignment, you'll be working with 3D MRI brain scans from the public Medical Segmentation Decathlon challenge project. This is an incredibly rich dataset that provides you with labels associated with each point (voxel) inside a 3D representation of a patient's brain. Ultimately, in this week's assignment, you will train a neural network to make three-dimensional spatial segmentation predictions for common brain disorders.
In this notebook, you're all set up to explore this exciting dataset. Run the code below and tweak it to explore further!
Import packages
For this lab, you'll import some of the packages you've seen before (numpy
, matplotlib
and seaborn
) as well as some new ones for reading (nibabel
) and visualizing (itk
, itkwidgets
, ipywidgets
) the data. Run the next cell to import these packages.
# Import all the necessary packages
import numpy as np
import nibabel as nib
import itk
import itkwidgets
from ipywidgets import interact, interactive, IntSlider, ToggleButtons
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set_style('darkgrid')
Loading Images of the brain
Run the next cell to grab a single 3D MRI brain scan