dicomViewer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from ipywidgets import interact_manual, interact\n",
    "import os\n",
    "from pydicom import dcmread\n",
    "from ipywidgets import widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_dicom_image(med_img, title=\"\"):\n",
    "    plt.figure(figsize=(15, 7))\n",
    "    plt.imshow(med_img, cmap='gray')\n",
    "    plt.title(title)\n",
    "    plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_dicom_image(file_path):\n",
    "    medical_image = dcmread(file_path)\n",
    "    pixel_array = medical_image.pixel_array\n",
    "    return medical_image, pixel_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def image_transformation(pixel_array):\n",
    "    upper_bound = int(pixel_array.max())\n",
    "\n",
    "    row, col = pixel_array.shape\n",
    "    c = 1\n",
    "    #b = 1.35\n",
    "    b = 100\n",
    "\n",
    "    output_img = pixel_array**b\n",
    "\n",
    "    return output_img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_image_histogram(img, img2):\n",
    "    plt.figure(figsize=(15, 5)) \n",
    "    plt.subplot(1,2,1)\n",
    "    plt.imshow(img,cmap='gray')\n",
    "    plt.title('image')\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "\n",
    "    plt.subplot(1,2,2)\n",
    "    plt.imshow(img,cmap='gray')\n",
    "    plt.title('image')\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "folder_dir = \"../Database/2EFVJVCN-Kmeans\"\n",
    "\n",
    "all_images = []\n",
    "\n",
    "for file in os.listdir(folder_dir):\n",
    "    all_images.append(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main(index):\n",
    "    dicom_image, pixel_array = read_dicom_image(f'{folder_dir}/{all_images[index]}')\n",
    "    plot_image_histogram(pixel_array, image_transformation(pixel_array))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#index=widgets.IntSlider(min=0, max=len(all_images)-1, step=1, value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fec188e0a9e3492a98d57ab9f4f5b2e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Play(value=0, description='Press play', max=357), IntSlider(value=0, max=357)))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "play = widgets.Play(\n",
    "    value=0,\n",
    "    min=0,\n",
    "    max=len(all_images)-1,\n",
    "    step=1,\n",
    "    nterval=10000000,\n",
    "    description=\"Press play\",\n",
    "    disabled=False\n",
    ")\n",
    "slider = widgets.IntSlider(min=0, max=len(all_images)-1, step=1, value=0)\n",
    "widgets.jslink((play, 'value'), (slider, 'value'))\n",
    "\n",
    "widgets.HBox([play, slider])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ab7a8f066db34865b12a6a972c60d8af",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(IntSlider(value=0, description='index', max=357), Output()), _dom_classes=('widget-inter…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.main(index)>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact(main, index=slider)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I5700000'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_images[312]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I5500000'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_images[310]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I3530000'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_images[284]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I3520000'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_images[283]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I3510000'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_images[282]"
   ]
  }
 ],
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