{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "

Assignment 3

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Medical Image Segmentation, SVM and Robust PCA

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Given date: Thursday November 14
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Due date: Friday December 9
\n", "\n", " \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Question 1 (6pts). \n", "\n", "In this first part, we will rely on K-means to identify the white matter, gray matter and the Cerebrospinal Fluid (CSF) on T1 Magnetic Resonance Images. Start by downloading the files 't1_ai_msles2_1mm_pn3_rf0.mnc.gz' and 't1_icbm_normal_1mm_pn1_rf0.mnc.gz' from github. To open those files, you will need the nibabel package (you can install this package using the command 'pip install nibabel' from the command line). Once the package is installed, use the lines below to visualize the images. \n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import nibabel as nib\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "img = nib.load('t1_icbm_normal_1mm_pn1_rf0.mnc')\n", "data = img.get_fdata()\n", "plt.imshow(data[90,:,:])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Take your training image to be frame 90 as above. We will start by removing the skull from the image. In order to get an idea of the pixels distribution, plot the histogram of the image using the 'hist' function from pyplot." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "### \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once you have the histogram, use this histogram to generate a binary version of the image. For this you can for example rely on the 'threshold' function from opencv. Determine the threshold (approximately) from the histogram so that the background pixels are set to 0 and the skull/head pixels (i.e. skull included) are set to 1 (as much as possible)." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# put your code here\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To get rid of the remaining black pixels located inside the head, we can use the functions 'erode' and 'dilate' from opencv. Dilate will increase the size of any white region while erode will shrink those regions. You can choose a 5x5 filter for both morphological operators. PLay a little with the filter size to determine the optimal combination of filter for the removing of the skull" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# put your code here\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once you have the mask for the head, shrink it a little more to get rid of the skull (The mask might be defined as taking values in [0,255] with 0 being black and 255 being white). Transform it to {0,1}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# put your code here\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Get the final (skull free) image by multiplying your original image with the mask" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# put your code here\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Recalculate the histogram and find the (approximate) centers of each class. To get a clearer picture of the classes, you might want to use np.where and np.delete to remove the background pixels (those taking values sufficiently close to 0)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "### put your code here" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, apply the Kmeans algorithm (with K=3) to the image obtained by removing the background pixels. Display the final result" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from sklearn.cluster import KMeans\n", "\n", "\n", "# put your code here\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Question II (10pts): Max margin classifiers and outliers\n", "\n", "Consider the dataset below. We would like to learn a classifier for this dataset that maximizes the margin (i.e. such that the distance between the closest points to the classifier is maximized). We have seen that one can solve this problem by means of the constrained formulation\n", "\n", "\\begin{align*}\n", "\\min_{\\mathbf{\\beta}} \\quad & \\|\\mathbf{\\beta}\\|^2 \\\\\n", "\\text{subject to} \\quad & y(\\mathbf{x}^{(i)})t^{(i)} \\geq 1 \n", "\\end{align*}\n", "\n", "where $y(\\mathbf{x}^{(i)}) = \\mathbf{\\beta}^T\\mathbf{x}^{(i)} + \\beta_0$. We might sometimes want to use a (softer) unconstrained formulation. in particular, when selecting this option, we can use the following function known as the _Hinge loss_ \n", "\n", "\\begin{align*}\n", "\\max(0, 1-t^{(i)}y(\\mathbf{x}^{(i)})) = \\max(0, 1-t^{(i)}(\\mathbf{\\beta}^T\\mathbf{x}^{(i)}+\\beta_0))\n", "\\end{align*}\n", "\n", "For such a loss, we can derive a softer, unconstrained version of the problem as \n", "\n", "\\begin{align*}\n", "\\min_{\\mathbf{\\beta}} \\quad & \\|\\mathbf{\\beta}\\|^2 + \\frac{C}{N}\\sum_{i=1}^N \\max(0, 1-t^{(i)}(\\mathbf{\\beta}^T\\mathbf{x}^{(i)}+\\beta_0))\n", "\\end{align*}\n", "\n", "In short we penalize a point only if this point lies on the wrong side of the plane." ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import scipy.io\n", "\n", "from scipy.io import loadmat\n", "pointsClass1 = scipy.io.loadmat('points_class1_Lab2_Ex1.mat')['points_class1_Lab2_Ex1']\n", "pointsClass2 = scipy.io.loadmat('points_class2_Lab2_Ex1.mat')['points_class2_Lab2_Ex1']\n", "\n", "\n", "plt.scatter(pointsClass1[:,0], pointsClass1[:,1], c='r')\n", "plt.scatter(pointsClass2[:,0], pointsClass2[:,1], c='b')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Question II.a (3pts)\n", "\n", "Start by completing the function below which should return the value and gradient of the hinge loss at a point $\\mathbf{x}^{(i)}$. What is the gradient of the hinge loss?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "def HingeLoss(x, t, beta):\n", " \n", " '''Returns the value and gradient of the hinge \n", " loss at the point x'''\n", " \n", " return value, gradient" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Question II.b (7pts)\n", "\n", "Once you have the function, implement a function HingeLossSVC that takes as input a starting weight vector $\\mathbf{\\beta}$ and intercept $\\beta_0$ as well as the set of training points and a value for the parameter $C$ and returns the maximum margin classifier. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def HingeLossSVC(beta_init, training, C, targets):\n", " \n", " '''Returns the maximal margin classifier for the \n", " training dataset'''\n", " \n", "\n", " return beta" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Question III (10pts): Robust PCA for video surveillance \n", "\n", "Principal Component Analysis (PCA) retains an approximation of an original dataset $X$ by focusing on the largest singular values. Such an order $K$ approximation can be obtained from the singular value decomposition $\\boldsymbol U \\boldsymbol \\Sigma \\boldsymbol V^T$ by truncating $\\boldsymbol U$ to the first $K$ columns, retaining the $K\\times K$ diagonal matrix $\\boldsymbol \\Sigma_k$ as well as the first $K$ rows of $\\boldsymbol V^T$, $\\boldsymbol V_k^T$, and writing the approximation as $\\boldsymbol U_k \\boldsymbol \\Sigma_k \\boldsymbol V^T_k$. This approach is particularly efficient when each of the feature vectors (or images in this case) are close to each other. When there are sharp variations across images, such as when an object appears, move throughout the images and then disapears, a simple PCA does not suffice anymore and one might want to extend it to something more robust. The escalator sequence below is an example of such sequence (the movie can be found on github). " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(20800,)\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import cv2\n", "import matplotlib.pyplot as plt\n", "\n", "# read video\n", "\n", "import scipy.io\n", "movie = scipy.io.loadmat('escalator_data.mat')\n", "#frame0 = \n", "print(np.shape(movie['X'][:,0]))\n", "\n", "plt.imshow(movie['X'][:,0].reshape((160,130)).swapaxes(0, 1), cmap='gray')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The idea of Robust PCA is to add a \"sparse\" component to the traditional PCA decomposition. Given a collection of images that we store as the columns of the matrix $X$, one then looks for a decomposition\n", " \n", "\\begin{align} \n", "\\boldsymbol X = \\boldsymbol Y + \\boldsymbol S\n", "\\end{align}\n", "\n", "Where $Y$ is a matrix which contains the original PCA decomposition, and thus encodes the part of the images that remains approximately constant throughout the sequence (background), and $\\boldsymbol S$ is the sparse part (i.e a sequence of images that are varying through the sequence but only at a small number of pixel positions in the images (foreground), in other words most of the pixels in $S$ are assumed to be zero). To recover each part one approach is to proceed as follows, see [Candes et al.](https://arxiv.org/pdf/0912.3599.pdf)\n", "\n", "We let $\\mu$ to denote the parameter that controls the amount of dara we want to store in the sparse foreground extraction part, $\\boldsymbol S$. A good choice is to take $\\mu = n_1n_2/4\\|\\mathbf{X}\\|_1$ where $\\mathbf{X}\\in\\mathbb{R}^{n_1\\times n_2}$ encodes the video surveillance sequence (each frame being stacked as a column of $\\mathbf{X}$) and $\\|\\mathbf{X}\\|_1$ denotes the entry wise $\\ell_1$ norm of $\\mathbf{X}$, $\\mathbf{X} = \\sum_{ij} |X_{ij}|$\n", "\n", "The algorithm then proceeds as follows\n", "\n", "\n", "__Initialize__ $Y$, $S$ to $0$\n", "\n", "__Step 1.__ Compute the truncated SVD of the matrix $X - S - \\mu^{-1}Y$, i.e. let $X - S - \\mu^{-1}Y = U\\Sigma V^T$. The truncated SVD is then obtained by replacing the diagonal matrix of singular values with the truncation \n", "$$ \n", "\\sigma \\leftarrow \\text{sign}(\\sigma)\\max(|\\sigma| - \\mu, 0) \n", "$$\n", "\n", "and store it in $L$, $L = SVD_{\\mu}(X - S - \\mu^{-1}Y)$ \n", "\n", "\n", "\n", "__Step 2.__ Apply the thresholding operator $f(x) = \\text{sign}(x)\\max(|x| - \\lambda \\mu, 0) $ with threshold $\\lambda\\mu$ to the entries of the matrix $X - L + \\mu^{-1}Y$ and store the result in $\\mathbf{S}$.\n", "\n", "__Step 3.__ Update the matrix $Y$ as $Y \\leftarrow Y + \\mu(X - L - S)$\n", "\n", "\n", "A good approach to initialize the parameters is to take $lambda = 1/\\max(n_1,n_2)$ where $\\max(n_1,n_2)$ is the max number of rows or columns of the data matrix. One can also terminate the algorithm when $\\|X-L-S\\|_F \\leq \\delta \\|X\\|_F$ where $\\|X\\|_F$ is the Frobenius norm of the matrix and $\\delta$ can be taken for example as $10^{-7}$. \n", "\n", "\n", "Additional indications: if computing the full SVD from linalg is too expensive, you can replace it with the fast randomized PCA from facebook (see [fbpca](https://fbpca.readthedocs.io/en/latest/)) or a sparse SVD.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Question 3.a. (8pts) Complete the code below which separates the sparse part from the PCA decomposition" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np \n", "from __future__ import division\n", "from scipy.sparse.linalg import svds\n", "\n", "\n", "\n", "def robustPCA(X, delta=1e-6, mu=None, maxiter=500):\n", "\n", " '''\n", " The function should return a PCA like part stored in 'L' with only a few singular values \n", " that are non zero and a sparse sequence 'S' in which the images are black except w very \n", " limited number of pixels\n", " '''\n", " \n", " # Initialize the tuning parameters.\n", " lam = # put your value for lambda\n", " if mu is None:\n", " \n", " # complete with your value for mu\n", " \n", " # Convergence criterion.\n", " norm = np.sum(X ** 2)\n", "\n", " # Iterate.\n", " i = 0\n", " rank = np.min(shape)\n", " S = np.zeros(shape)\n", " Y = np.zeros(shape)\n", " while i < max(maxiter, 1):\n", " \n", " \n", " # Step 1. Compute and truncate the SVD\n", " \n", " \n", "\n", " # Step 2. Truncate the entries of X - L + mu^(-1)Y \n", " \n", "\n", " # Step 3. Update the matrix Y\n", " \n", " \n", "\n", " # Convergence criterion\n", " err = np.sqrt(np.sum(step ** 2) / norm)\n", " if err < delta:\n", " break\n", " i += 1\n", "\n", " if i >= maxiter:\n", " break\n", " \n", " return L, S" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Question 3.b. (2pts) \n", "\n", "Apply your function to the escalator sequence and display the result on at least one frame. Use subplot to display the extracted background and its corresponding foreground side by side. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# put your code here" ] } ], "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }