--- a +++ b/1. Applying AI to 2D Medical Imaging Data/6. Differentiate Between Models Exercise/solution.ipynb @@ -0,0 +1,498 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import scipy.stats\n", + "\n", + "import skimage\n", + "from skimage import io\n", + "import glob\n", + "\n", + "import sklearn\n", + "from scipy.ndimage import gaussian_filter" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## First we'll do background segmentation:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "## Read in two mammo images: \n", + "dense = io.imread('dense/mdb003.pgm')\n", + "fatty = io.imread('fatty/mdb005.pgm')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.image.AxesImage at 0x7f7c07a66d90>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(dense)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.image.AxesImage at 0x7f7c078a1510>" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(fatty)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = plt.hist(dense.ravel(),bins=256)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = plt.hist(fatty.ravel(),bins=256)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "## Next, experiment with different cut-off intensity thresholds to try to separate the background of the image\n", + "## From the histograms above, we might want to start with zero: \n", + "\n", + "thresh = 50\n", + "\n", + "dense_bin = (dense > thresh) * 255\n", + "fatty_bin = (fatty > thresh) * 255" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.image.AxesImage at 0x7f7c070c4ad0>" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(dense_bin)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.image.AxesImage at 0x7f7c070ae590>" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(fatty_bin)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Experiment with different values of 'thresh' above until you are satisfied that you are able to create a reasonable separation of tissue from background.\n", + "\n", + "One image pre-processing trick you might try before binarizing is _smoothing_ which you perform with a gaussian filter. Try adding the following step before binarization: \n", + "\n", + "img_smooth = gaussian_filter(img, sigma = 5)\n", + "\n", + "Where changing the value of _sigma_ will change the amount of smoothing. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Once you have chosen your value of threshold, let's use it to see if we can classify dense v. fatty breast tissue: " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "## Let's first get all of the intensity values of the breast tissue for our fatty breast images using the\n", + "## segmentation method above: \n", + "thresh = 50\n", + "\n", + "fatty_imgs = glob.glob(\"fatty/*\")\n", + "dense_imgs = glob.glob(\"dense/*\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "fatty_intensities = []\n", + "\n", + "for i in fatty_imgs: \n", + " \n", + " img = plt.imread(i)\n", + " img_mask = (img > thresh)\n", + " fatty_intensities.extend(img[img_mask].tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = plt.hist(fatty_intensities,bins=256)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "dense_intensities = []\n", + "\n", + "for i in dense_imgs: \n", + " \n", + " img = plt.imread(i)\n", + " img_mask = (img > thresh)\n", + " dense_intensities.extend(img[img_mask].tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = plt.hist(dense_intensities,bins=256)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "140" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scipy.stats.mode(fatty_intensities)[0][0]" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "176" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scipy.stats.mode(dense_intensities)[0][0]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fatty\n", + "Dense\n", + "Dense\n", + "Fatty\n", + "Fatty\n", + "Fatty\n", + "Fatty\n", + "Dense\n", + "Fatty\n", + "Fatty\n" + ] + } + ], + "source": [ + "for i in fatty_imgs: \n", + " \n", + " img = plt.imread(i)\n", + " img_mask = (img > thresh)\n", + " \n", + " fatty_delta = scipy.stats.mode(img[img_mask])[0][0] - scipy.stats.mode(fatty_intensities)[0][0]\n", + " dense_delta = scipy.stats.mode(img[img_mask])[0][0] - scipy.stats.mode(dense_intensities)[0][0]\n", + " \n", + " if (np.abs(fatty_delta) < np.abs(dense_delta)):\n", + " print(\"Fatty\")\n", + " else:\n", + " print(\"Dense\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Dense\n", + "Dense\n", + "Dense\n", + "Dense\n", + "Dense\n", + "Dense\n", + "Dense\n", + "Dense\n", + "Dense\n", + "Dense\n" + ] + } + ], + "source": [ + "for i in dense_imgs: \n", + " \n", + " img = plt.imread(i)\n", + " img_mask = (img > thresh)\n", + " \n", + " fatty_delta = scipy.stats.mode(img[img_mask])[0][0] - scipy.stats.mode(fatty_intensities)[0][0]\n", + " dense_delta = scipy.stats.mode(img[img_mask])[0][0] - scipy.stats.mode(dense_intensities)[0][0]\n", + " \n", + " if (np.abs(fatty_delta) < np.abs(dense_delta)):\n", + " print(\"Fatty\")\n", + " else:\n", + " print(\"Dense\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Just by using this method, we're able to get 100% accuracy on dense images and 70% accuracy on fatty images! Now, we 'trained' on the same set of images that we validated on, so in order to be confident in this algorithm we need to validated on a separate held out set, which we'll learn about in the next lesson. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import shutil\n", + "shutil.make_archive('models', 'zip', './')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}