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   "source": [
    "# 4. Thresholding exercises"
   ]
  },
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   "source": [
    "1. Import the relevant packages: numpy, matplotlib and skimage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Import the same image from this url address: https://cildata.crbs.ucsd.edu/media/images/13585/13585.tif\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Create a new variable called ```image_green``` that contains only the green channel by slicing the array"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Plot this image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Plot a histogram of the image"
   ]
  },
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   "source": [
    "6. Try to determine an appropriate threshold to recover the large structures in the image, create the corresponding mask and plot it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7. There are other algorithms for thresholding than the one of Otsu. Try to find one in the [Scikit-image documentation](http://scikit-image.org/docs/dev/api/skimage.filters.html) and to use it"
   ]
  },
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