How to run -> Readme, major edits

adasegroup · Sep 7, 2020 · 275ecf1 · 275ecf1
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diff --git a/README.md b/README.md
@@ -13,6 +13,14 @@ This course is specifically aimed at MSc and PhD students with basic knowledge o
  * Before seminar you are to install Docker https://www.docker.com/
 * SEMINAR 1 (04.09) EEG analysis, Machine Learning in EEG
 * SEMINAR 2 (04.09) MRI data analysis, sources, databases, tools 
+  * Before seminar, please, do the following:
+    1) Download data from link https://drive.google.com/drive/folders/1P0ZhS1EoDY6fncnJb7foNFPjY5uoN6r0?usp=sharing
+    2) Clone repository to your local machine
+    3) Run docker locally and ensure it working with command `docker run hello-world`
+    4) In terminal: `cd to NEUROML/seminar2`
+    5) Type command `docker build -t neuroml/seminar2:0.0.1` and wait for successfull build
+    6) Run `docker run --rm -it -v /directory/to/downloaded/data:/workspace/data -p 8080:8080 neuroml/seminar2:0.0.1
+    7) Open browser (preferebly Chrome) -> localhost:8080
   * Before the seminar you are to install FreeSurfer https://surfer.nmr.mgh.harvard.edu/
 * SEMINAR 3 (04.09) Machine Learning for structural MRI data analysis
   * Before the seminar you are to get an account and granted access here https://db.humanconnectome.org/data/projects/HCP_1200

diff --git a/seminar2/Dockerfile b/seminar2/Dockerfile
@@ -38,11 +38,30 @@ RUN apt-get update -qq \
            grep \
            less \
            wget \
-           bzip2 \
            make \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 
+ENV PATH="/opt/dcm2niix-latest/bin:$PATH"
+RUN apt-get update -qq \
+    && apt-get install -y -q --no-install-recommends \
+           cmake \
+           g++ \
+           gcc \
+           git \
+           make \
+           pigz \
+           zlib1g-dev \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/* \
+    && git clone https://github.com/rordenlab/dcm2niix /tmp/dcm2niix \
+    && mkdir /tmp/dcm2niix/build \
+    && cd /tmp/dcm2niix/build \
+    && cmake  -DCMAKE_INSTALL_PREFIX:PATH=/opt/dcm2niix-latest .. \
+    && make \
+    && make install \
+    && rm -rf /tmp/dcm2niix
+
 ENV ANTSPATH="/opt/ants-2.2.0" \
     PATH="/opt/ants-2.2.0:$PATH"
 RUN echo "Downloading ANTs ..." \
@@ -102,6 +121,7 @@ RUN export PATH="/opt/miniconda-latest/bin:$PATH" \
            'nilearn' \
            'traits' \
            'nipype' \
+           'seaborn' \
     && sync && conda clean --all && sync
 
 RUN wget https://ftpmirror.gnu.org/parallel/parallel-20190222.tar.bz2 \
@@ -120,8 +140,6 @@ COPY ./entrypoint.sh /entrypoint.sh
 RUN chmod +x /workspace/multiproc.sh \
             /entrypoint.sh
 
-
-
 RUN "/neurodocker/startup.sh"
 
 #RUN "./${FREESURFER_HOME}/SetUpFreeSurfer.sh"
@@ -142,6 +160,13 @@ RUN echo '{ \
     \n      ] \
     \n    ], \
     \n    [ \
+    \n      "dcm2niix", \
+    \n      { \
+    \n        "version": "latest", \
+    \n        "method": "source" \
+    \n      } \
+    \n    ], \
+    \n    [ \
     \n      "ants", \
     \n      { \
     \n        "version": "2.2.0" \

diff --git a/seminar2/entrypoint.sh b/seminar2/entrypoint.sh
@@ -1,9 +1,9 @@
 #! /bin/bash
 
-printf 'Neurodocker startup - success'
+printf 'Neurodocker startup - success\n'
 
 source $FREESURFER_HOME/SetUpFreeSurfer.sh
 
-printf 'FREESURFER - check' 
+printf 'FREESURFER - check\n' 
 
 ./opt/miniconda-latest/envs/neuro/bin/jupyter-lab --ip=0.0.0.0 --port=8080 --no-browser --allow-root --notebook-dir='/workspace' --NotebookApp.token=''
diff --git a/seminar2/seminar2_1_mri.ipynb b/seminar2/seminar2_1_mri.ipynb
@@ -1,5 +1,20 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "PLAN:\n",
+    "\n",
+    "1) MRI data formats\n",
+    "2) accessing data voxel and meta data\n",
+    "3) transformations\n",
+    "4) preprocessing\n",
+    "5) visualization\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -428,7 +443,45 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "*Voxel size* and *Pixel spacing* are important as we for preprocessing we can use only isomorphic voxel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Assume that you recieved new dicom from hospital and you need to convert to convinient NIFTI, let's review the tool distinctive from simple on above:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!dcm2niix -o /workspace -f %i_%n_%p -z y /workspace/data/DICOM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from nilearn.input_data import NiftiMasker\n",
+    "from nilearn import plotting\n",
+    "dcm_to_nii_convert = './1010_BRAIN_MR_T1_AX.nii.gz'\n",
+    "plot_convert = plotting.view_img(dcm_to_nii_convert,\n",
+    "                                 bg_img=False,\n",
+    "                                 cmap='gray',\n",
+    "                                 symmetric_cmap=False,\n",
+    "                                 threshold=0,\n",
+    "                                 title='Drag mouse to go through slices')\n",
+    "plot_convert"
+   ]
   }
  ],
  "metadata": {
@@ -452,4 +505,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
diff --git a/seminar2/seminar2_2_transform.ipynb b/seminar2/seminar2_2_transform.ipynb
@@ -10,6 +10,13 @@
     "warnings.filterwarnings('ignore')\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"./assets/affine_1.png\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -88,7 +95,7 @@
     "mni_space_template = nib.load('/workspace/data/mni_icbm152_t1_tal_nlin_sym_09a.nii')  # Full template\n",
     "\n",
     "nilearn.plotting.plot_anat(nii_file,\n",
-    "                           title='Nifti T1 Native Space')\n",
+    "                           title='Nifti T1 Native Space', annotate=True)\n",
     "\n",
     "nilearn.plotting.plot_anat(mni_space_template,\n",
     "                           title='Nifti MNI152 Space')\n",
@@ -154,6 +161,103 @@
     "\"\"\".format(nii_file.shape, mni_space_template.shape))\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can think of the image affine as a combination of a series of transformations to go from voxel coordinates to mm coordinates in terms of the magnet isocenter. Here is the EPI affine broken down into a series of transformations, with the results shown on the localizer image:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"./assets/affine_2.png\">"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from nibabel.affines import from_matvec, to_matvec, apply_affine\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "reflect = np.array([[1, 0, 0],\n",
+    "                    [0, 1, 0],\n",
+    "                    [0, 0, 1]])\n",
+    "\n",
+    "translate_affine = from_matvec(reflect, [0, 0, 0])  # reflect + shift 10 x direction\n",
+    "translate_affine"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transformed = np.dot(nii_file.get_qform(), translate_affine)\n",
+    "#nii_file.affine = transformed\n",
+    "print(transformed)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "header_info = nii_file.header\n",
+    "vox_data = np.array(nii_file.get_fdata())\n",
+    "transformed_nii = nib.Nifti1Image(vox_data, transformed, header_info)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tranfsorm_image = nilearn.plotting.plot_anat(transformed_nii,\n",
+    "                           title='Space displacement', annotate=True)\n",
+    "tranfsorm_image.add_overlay(nii_file, threshold=0.1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transform_image = nilearn.plotting.plot_anat(transformed_nii,\n",
+    "                           title='Space displacement', annotate=True)\n",
+    "transform_image.add_overlay(nii_file,threshold=0.8e3, colorbar=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "How about rotation?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cos_gamma = np.cos(0.3)\n",
+    "sin_gamma = np.sin(0.3)\n",
+    "rotation_affine = np.array([[1, 0, 0, 0],\n",
+    "                            [0, cos_gamma, -sin_gamma, 0],\n",
+    "                            [0, sin_gamma, cos_gamma, 0],\n",
+    "                            [0, 0, 0, 1]])"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},