{

 "cells": [

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "# 3. Classify Detected Nodules in LIDC Dataset as FP or TP\n",

    "\n",

    "## Summary\n",

    "\n",

    "* Load processed data into trained u-net to generate predicted nodule masks\n",

    "* Use nodule coordinates file (list3_2.csv) to label detected nodules as TP or FP\n",

    "* Load images for each respective detected nodule and train a CNN with the TP or FP labels"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 6,

   "metadata": {},

   "outputs": [

    {

     "name": "stderr",

     "output_type": "stream",

     "text": [

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:73: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:75: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:78: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(64, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:80: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(64, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:83: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(128, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:85: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(128, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:88: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(256, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:90: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(256, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:93: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(512, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:95: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(512, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:97: UserWarning: The `merge` function is deprecated and will be removed after 08/2017. Use instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc.\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\keras\\legacy\\layers.py:458: UserWarning: The `Merge` layer is deprecated and will be removed after 08/2017. Use instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc.\n",

      "  name=name)\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:99: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(256, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:100: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(256, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:102: UserWarning: The `merge` function is deprecated and will be removed after 08/2017. Use instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc.\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:104: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(128, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:105: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(128, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:107: UserWarning: The `merge` function is deprecated and will be removed after 08/2017. Use instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc.\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:109: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(64, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:110: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(64, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:112: UserWarning: The `merge` function is deprecated and will be removed after 08/2017. Use instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc.\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:114: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:115: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), padding=\"same\", activation=\"relu\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:116: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(1, (1, 1), activation=\"sigmoid\")`\n",

      "c:\\programdata\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel_launcher.py:118: UserWarning: Update your `Model` call to the Keras 2 API: `Model(inputs=Tensor(\"in..., outputs=Tensor(\"co...)`\n"

     ]

    }

   ],

   "source": [

    "#EDIT HERE##############################\n",

    "\n",

    "list32file=\"LIDC/list3.2.csv\"\n",

    "metafile=\"LIDC/LIDC-IDRI_MetaData.csv\"\n",

    "unetweightspath=\"modelweights/unet-weights-improvement.hdf5\"\n",

    "truenoduleweightspath=\"modelweights/truenodule-cnn-weights-improvement.hdf5\"\n",

    "datafolder=\"processeddata\"\n",

    "DOIpath='LIDC/DOI/'\n",

    "########################################\n",

    "\n",

    "\n",

    "import numpy as np # linear algebra\n",

    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",

    "import matplotlib.pyplot as plt\n",

    "import dicom\n",

    "import os\n",

    "import scipy.ndimage\n",

    "import time\n",

    "from keras.callbacks import ModelCheckpoint\n",

    "import h5py\n",

    "from sklearn.cluster import KMeans\n",

    "from skimage import measure, morphology\n",

    "from mpl_toolkits.mplot3d.art3d import Poly3DCollection\n",

    "import cell_magic_wand as cmw\n",

    "from glob import glob\n",

    "import random\n",

    "from sklearn.model_selection import train_test_split\n",

    "import keras\n",

    "from keras.models import Sequential,load_model,Model\n",

    "from keras.layers import Dense, Dropout, Activation, Flatten\n",

    "from keras.layers import Conv2D, MaxPooling2D, SpatialDropout2D\n",

    "from keras.layers import Input, merge, UpSampling2D, BatchNormalization\n",

    "from keras.optimizers import Adam\n",

    "from keras.callbacks import EarlyStopping, ModelCheckpoint\n",

    "from keras import backend as K\n",

    "from keras.utils import to_categorical\n",

    "from keras.datasets import mnist\n",

    "from keras.models import Sequential\n",

    "from keras import backend as K\n",

    "from keras.optimizers import Adam\n",

    "K.set_image_dim_ordering('th') \n",

    "nodulelocations=pd.read_csv(list32file)\n",

    "meta=pd.read_csv(metafile)\n",

    "\n",

    "meta=meta.drop(meta[meta['Modality']!='CT'].index)\n",

    "meta=meta.reset_index()\n",

    "\n",

    "#Get folder names of CT data for each patient\n",

    "patients=[DOIpath+meta['Patient Id'][i] for i in range(len(meta))]\n",

    "datfolder=[]\n",

    "for i in range(0,len(meta)-1):\n",

    "    for path in os.listdir(patients[i]):\n",

    "        if os.path.exists(patients[i]+'/'+path+'/'+meta['Series UID'][i]):\n",

    "            datfolder.append(patients[i]+'/'+path+'/'+meta['Series UID'][i])\n",

    "patients=datfolder\n",

    "\n",

    "#Load nodules locations\n",

    "\n",

    "#Code sourced from https://www.kaggle.com/c/data-science-bowl-2017#tutorial\n",

    "smooth = 1.0\n",

    "width = 32\n",

    "\n",

    "def dice_coef(y_true, y_pred):\n",

    "    y_true_f = K.flatten(y_true)\n",

    "    y_pred_f = K.flatten(y_pred)\n",

    "    intersection = K.sum(y_true_f * y_pred_f)\n",

    "    return (2. * intersection + smooth) / (K.sum(y_true_f) + K.sum(y_pred_f) + smooth)\n",

    "def dice_coef_loss(y_true, y_pred):\n",

    "    return -dice_coef(y_true, y_pred)\n",

    "\n",

    "def unet_model():\n",

    "    inputs = Input((1, 512, 512))\n",

    "    conv1 = Conv2D(width, 3, 3, activation='relu', border_mode='same')(inputs)\n",

    "    conv1 = BatchNormalization(axis = 1)(conv1)\n",

    "    conv1 = Conv2D(width, 3, 3, activation='relu', border_mode='same')(conv1)\n",

    "    pool1 = MaxPooling2D(pool_size=(2, 2))(conv1)\n",

    "\n",

    "    conv2 = Conv2D(width*2, 3, 3, activation='relu', border_mode='same')(pool1)\n",

    "    conv2 = BatchNormalization(axis = 1)(conv2)\n",

    "    conv2 = Conv2D(width*2, 3, 3, activation='relu', border_mode='same')(conv2)\n",

    "    pool2 = MaxPooling2D(pool_size=(2, 2))(conv2)\n",

    "\n",

    "    conv3 = Conv2D(width*4, 3, 3, activation='relu', border_mode='same')(pool2)\n",

    "    conv3 = BatchNormalization(axis = 1)(conv3)\n",

    "    conv3 = Conv2D(width*4, 3, 3, activation='relu', border_mode='same')(conv3)\n",

    "    pool3 = MaxPooling2D(pool_size=(2, 2))(conv3)\n",

    "\n",

    "    conv4 = Conv2D(width*8, 3, 3, activation='relu', border_mode='same')(pool3)\n",

    "    conv4 = BatchNormalization(axis = 1)(conv4)\n",

    "    conv4 = Conv2D(width*8, 3, 3, activation='relu', border_mode='same')(conv4)\n",

    "    pool4 = MaxPooling2D(pool_size=(2, 2))(conv4)\n",

    "\n",

    "    conv5 = Conv2D(width*16, 3, 3, activation='relu', border_mode='same')(pool4)\n",

    "    conv5 = BatchNormalization(axis = 1)(conv5)\n",

    "    conv5 = Conv2D(width*16, 3, 3, activation='relu', border_mode='same')(conv5)\n",

    "\n",

    "    up6 = merge([UpSampling2D(size=(2, 2))(conv5), conv4], mode='concat', concat_axis=1)\n",

    "    conv6 = SpatialDropout2D(0.35)(up6)\n",

    "    conv6 = Conv2D(width*8, 3, 3, activation='relu', border_mode='same')(conv6)\n",

    "    conv6 = Conv2D(width*8, 3, 3, activation='relu', border_mode='same')(conv6)\n",

    "\n",

    "    up7 = merge([UpSampling2D(size=(2, 2))(conv6), conv3], mode='concat', concat_axis=1)\n",

    "    conv7 = SpatialDropout2D(0.35)(up7)\n",

    "    conv7 = Conv2D(width*4, 3, 3, activation='relu', border_mode='same')(conv7)\n",

    "    conv7 = Conv2D(width*4, 3, 3, activation='relu', border_mode='same')(conv7)\n",

    "\n",

    "    up8 = merge([UpSampling2D(size=(2, 2))(conv7), conv2], mode='concat', concat_axis=1)\n",

    "    conv8 = SpatialDropout2D(0.35)(up8)\n",

    "    conv8 = Conv2D(width*2, 3, 3, activation='relu', border_mode='same')(conv8)\n",

    "    conv8 = Conv2D(width*2, 3, 3, activation='relu', border_mode='same')(conv8)\n",

    "\n",

    "    up9 = merge([UpSampling2D(size=(2, 2))(conv8), conv1], mode='concat', concat_axis=1)\n",

    "    conv9 = SpatialDropout2D(0.35)(up9)\n",

    "    conv9 = Conv2D(width, 3, 3, activation='relu', border_mode='same')(conv9)\n",

    "    conv9 = Conv2D(width, 3, 3, activation='relu', border_mode='same')(conv9)\n",

    "    conv10 = Conv2D(1, 1, 1, activation='sigmoid')(conv9)\n",

    "\n",

    "    model = Model(input=inputs, output=conv10)\n",

    "    model.compile(optimizer=Adam(lr=1e-5), loss=dice_coef_loss, metrics=[dice_coef])\n",

    "    return model\n",

    "\n",

    "model=unet_model()\n",

    "model.load_weights(unetweightspath)"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 2,

   "metadata": {

    "collapsed": true

   },

   "outputs": [],

   "source": [

    "# Load the scans in given folder path\n",

    "# code sourced from https://www.kaggle.com/gzuidhof/full-preprocessing-tutorial\n",

    "def load_scan(path):\n",

    "    slices = [dicom.read_file(path + '/' + s, force=True) for s in os.listdir(path) if s.endswith('.dcm')]\n",

    "    slices.sort(key = lambda x: float(x.ImagePositionPatient[2]), reverse=True)\n",

    "    try:\n",

    "        slice_thickness = np.abs(slices[0].ImagePositionPatient[2] - slices[1].ImagePositionPatient[2])\n",

    "    except:\n",

    "        slice_thickness = np.abs(slices[0].SliceLocation - slices[1].SliceLocation)\n",

    "        \n",

    "    for s in slices:\n",

    "        s.SliceThickness = slice_thickness\n",

    "        \n",

    "    return slices\n",

    "\n",

    "#convert to ndarray\n",

    "def get_pixels_hu(slices):\n",

    "    image = np.stack([s.pixel_array for s in slices])\n",

    "    # Convert to int16 (from sometimes int16), \n",

    "    # should be possible as values should always be low enough (<32k)\n",

    "    image = image.astype(np.int16)\n",

    "\n",

    "    # Set outside-of-scan pixels to 0\n",

    "    # The intercept is usually -1024, so air is approximately 0\n",

    "    image[image == -2000] = 0\n",

    "    \n",

    "    # Convert to Hounsfield units (HU)\n",

    "    for slice_number in range(len(slices)):\n",

    "        \n",

    "        intercept = slices[slice_number].RescaleIntercept\n",

    "        slope = slices[slice_number].RescaleSlope\n",

    "        \n",

    "        if slope != 1:\n",

    "            image[slice_number] = slope * image[slice_number].astype(np.float64)\n",

    "            image[slice_number] = image[slice_number].astype(np.int16)\n",

    "            \n",

    "        image[slice_number] += np.int16(intercept)\n",

    "    \n",

    "    return np.array(image, dtype=np.int16)\n",

    "\n",

    "def processimage(img):\n",

    "    #function sourced from https://www.kaggle.com/c/data-science-bowl-2017#tutorial\n",

    "    #Standardize the pixel values\n",

    "    mean = np.mean(img)\n",

    "    std = np.std(img)\n",

    "    img = img-mean\n",

    "    img = img/std\n",

    "    #plt.hist(img.flatten(),bins=200)\n",

    "    #plt.show()\n",

    "    #print(thresh_img[366][280:450])\n",

    "    middle = img[100:400,100:400] \n",

    "    mean = np.mean(middle)  \n",

    "    max = np.max(img)\n",

    "    min = np.min(img)\n",

    "    #move the underflow bins\n",

    "    img[img==max]=mean\n",

    "    img[img==min]=mean\n",

    "    kmeans = KMeans(n_clusters=2).fit(np.reshape(middle,[np.prod(middle.shape),1]))\n",

    "    centers = sorted(kmeans.cluster_centers_.flatten())\n",

    "    threshold = np.mean(centers)\n",

    "    thresh_img = np.where(img<threshold,1.0,0.0)  # threshold the image\n",

    "    eroded = morphology.erosion(thresh_img,np.ones([4,4]))\n",

    "    dilation = morphology.dilation(eroded,np.ones([10,10]))\n",

    "    labels = measure.label(dilation)\n",

    "    label_vals = np.unique(labels)\n",

    "    #plt.imshow(labels)\n",

    "    #plt.show()\n",

    "    labels = measure.label(dilation)\n",

    "    label_vals = np.unique(labels)\n",

    "    regions = measure.regionprops(labels)\n",

    "    good_labels = []\n",

    "    for prop in regions:\n",

    "        B = prop.bbox\n",

    "        if B[2]-B[0]<475 and B[3]-B[1]<475 and B[0]>40 and B[2]<472:\n",

    "            good_labels.append(prop.label)\n",

    "    mask = np.ndarray([512,512],dtype=np.int8)\n",

    "    mask[:] = 0\n",

    "    #\n",

    "    #  The mask here is the mask for the lungs--not the nodes\n",

    "    #  After just the lungs are left, we do another large dilation\n",

    "    #  in order to fill in and out the lung mask \n",

    "    #\n",

    "    for N in good_labels:\n",

    "        mask = mask + np.where(labels==N,1,0)\n",

    "    mask = morphology.dilation(mask,np.ones([10,10])) # one last dilation\n",

    "    return mask*img\n",

    "\n",

    "def processimagefromfile(ppix):\n",

    "    processpix=np.ndarray([ppix.shape[0],512,512])\n",

    "    for i in range(ppix.shape[0]):\n",

    "        processpix[i]=processimage(ppix[i])\n",

    "    return processpix\n",

    "\n",

    "#predict mask from images\n",

    "def predictmask(images):\n",

    "    images=images.reshape(images.shape[0],1,512,512)\n",

    "    num_test=images.shape[0]\n",

    "    imgs_mask_test = np.ndarray([num_test,1,512,512],dtype=np.float32)\n",

    "    for i in range(num_test):\n",

    "        imgs_mask_test[i] = model.predict([images[i:i+1]], verbose=0)[0]\n",

    "    return imgs_mask_test\n",

    "\n",

    "#find number of slices where a nodule is detected\n",

    "def getnoduleindex(imgs_mask_test):\n",

    "    masksum=[np.sum(maskslice[0]) for maskslice in imgs_mask_test]\n",

    "    return [i for i in range(len(masksum)) if masksum[i]>5]\n",

    "\n",

    "def nodule_coordinates(nodulelocations,meta):\n",

    "    slices=nodulelocations[\"slice no.\"][nodulelocations.index[nodulelocations[\"case\"]==int(meta[\"Patient Id\"][-4:])]]\n",

    "    xlocs=nodulelocations[\"x loc.\"][nodulelocations.index[nodulelocations[\"case\"]==int(meta[\"Patient Id\"][-4:])]]\n",

    "    ylocs=nodulelocations[\"y loc.\"][nodulelocations.index[nodulelocations[\"case\"]==int(meta[\"Patient Id\"][-4:])]]\n",

    "    nodulecoord=[]\n",

    "    for i in range(len(slices)):\n",

    "        nodulecoord.append([slices.values[i]-1,xlocs.values[i]-1,ylocs.values[i]-1])\n",

    "    return nodulecoord\n",

    "\n",

    "#generate nodule or non-nodule labels for mask predictions\n",

    "def truenodules(noduleindex,masks,nodulecoords):\n",

    "    label=[]\n",

    "    for ind in noduleindex:\n",

    "        for cord in nodulecoords:\n",

    "            if abs(ind-cord[0])<2:\n",

    "                com=scipy.ndimage.center_of_mass(masks[ind])\n",

    "                if abs(com[1]-cord[2])<2 and abs(com[2]-cord[1])<2:\n",

    "                    label.append(True)\n",

    "            else:\n",

    "                label.append(False)\n",

    "    return label\n",

    "    \n",

    "def slicecount(start,end):\n",

    "    slicecounts=[]\n",

    "    for i in range(start,end):\n",

    "        if len(nodule_coordinates(nodulelocations,meta.iloc[i]))>0:\n",

    "            patient_scan=load_scan(patients[i])\n",

    "            slicecounts.append(len(patient_scan))\n",

    "    return slicecounts"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 3,

   "metadata": {

    "scrolled": true

   },

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Processing patient# 197 ETA: 13.88888888888889 hrs\n",

      "Processing patient# 198 ETA: 1.1223869024034948e-08 hrs\n",

      "Processing patient# 199 ETA: 8.375600754116487e-09 hrs\n",

      "[[77, 132, 243]]\n",

      "1751    4.335\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.0\n",

      "Specificity: 0.0\n",

      "Processing patient# 200 ETA: 0.0 hrs\n",

      "[[44, 187, 235]]\n",

      "1752    7.684\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.0\n",

      "Specificity: 0.0\n",

      "Processing patient# 201 ETA: -0.00043430759374313906 hrs\n",

      "[[56, 220, 307], [48, 381, 246], [49, 170, 194], [135, 118, 191], [46, 375, 203], [50, 189, 192], [91, 150, 172]]\n",

      "1753     8.774\n",

      "1754     4.749\n",

      "1755     3.795\n",

      "1756     6.345\n",

      "1757     5.952\n",

      "1758    14.905\n",

      "1759     5.398\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 55 with actual coord [56, 220, 307]\n",

      "Nodule Detected at slice# 56 with actual coord [56, 220, 307]\n",

      "Nodule Detected at slice# 57 with actual coord [56, 220, 307]\n",

      "Nodule Detected at slice# 134 with actual coord [135, 118, 191]\n",

      "Nodule Detected at slice# 135 with actual coord [135, 118, 191]\n",

      "Nodule Detected at slice# 136 with actual coord [135, 118, 191]\n",

      "Nodule Detected at slice# 45 with actual coord [46, 375, 203]\n",

      "Nodule Detected at slice# 46 with actual coord [46, 375, 203]\n",

      "Nodule Detected at slice# 47 with actual coord [46, 375, 203]\n",

      "Nodule Detected at slice# 49 with actual coord [50, 189, 192]\n",

      "Nodule Detected at slice# 50 with actual coord [50, 189, 192]\n",

      "Nodule Detected at slice# 51 with actual coord [50, 189, 192]\n",

      "Nodule Detected at slice# 90 with actual coord [91, 150, 172]\n",

      "Nodule Detected at slice# 91 with actual coord [91, 150, 172]\n",

      "Nodule Detected at slice# 92 with actual coord [91, 150, 172]\n",

      "Sensitivity: 0.5555555555555556\n",

      "Specificity: 0.09375\n",

      "Processing patient# 202 ETA: -0.0012672066931152888 hrs\n",

      "[[281, 85, 162]]\n",

      "1760    4.91\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.5\n",

      "Specificity: 0.07042253521126761\n",

      "Processing patient# 203 ETA: -0.0029408619673968574 hrs\n",

      "[[246, 139, 150], [41, 316, 311], [88, 131, 345], [319, 201, 153], [109, 127, 352]]\n",

      "1761    6.328\n",

      "1762    3.915\n",

      "1763    3.396\n",

      "1764    6.653\n",

      "1765    3.547\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 245 with actual coord [246, 139, 150]\n",

      "Nodule Detected at slice# 246 with actual coord [246, 139, 150]\n",

      "Nodule Detected at slice# 247 with actual coord [246, 139, 150]\n",

      "Nodule Detected at slice# 318 with actual coord [319, 201, 153]\n",

      "Nodule Detected at slice# 319 with actual coord [319, 201, 153]\n",

      "Nodule Detected at slice# 320 with actual coord [319, 201, 153]\n",

      "Sensitivity: 0.4666666666666667\n",

      "Specificity: 0.07777777777777778\n",

      "Processing patient# 204 ETA: -0.005424329860537682 hrs\n",

      "[[253, 307, 392], [192, 181, 383], [210, 300, 385], [243, 470, 298], [96, 115, 198]]\n",

      "1766    4.072\n",

      "1767    5.395\n",

      "1768    4.111\n",

      "1769    3.864\n",

      "1770    5.376\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 191 with actual coord [192, 181, 383]\n",

      "Nodule Detected at slice# 192 with actual coord [192, 181, 383]\n",

      "Nodule Detected at slice# 193 with actual coord [192, 181, 383]\n",

      "Nodule Detected at slice# 95 with actual coord [96, 115, 198]\n",

      "Nodule Detected at slice# 96 with actual coord [96, 115, 198]\n",

      "Nodule Detected at slice# 97 with actual coord [96, 115, 198]\n",

      "Sensitivity: 0.45\n",

      "Specificity: 0.06870229007633588\n",

      "Processing patient# 205 ETA: -0.008036096493403116 hrs\n",

      "[[80, 164, 191]]\n",

      "1771    4.96\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.42857142857142855\n",

      "Specificity: 0.06537530266343826\n",

      "Processing patient# 206 ETA: -0.010317782699868935 hrs\n",

      "[[278, 426, 316]]\n",

      "1772    5.579\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 277 with actual coord [278, 426, 316]\n",

      "Nodule Detected at slice# 278 with actual coord [278, 426, 316]\n",

      "Nodule Detected at slice# 279 with actual coord [278, 426, 316]\n",

      "Sensitivity: 0.45454545454545453\n",

      "Specificity: 0.06593406593406594\n",

      "Processing patient# 207 ETA: -0.014129864809913658 hrs\n",

      "[[29, 356, 205], [14, 119, 289]]\n",

      "1773    3.940\n",

      "1774    4.346\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.4166666666666667\n",

      "Specificity: 0.06369426751592357\n",

      "Processing patient# 208 ETA: -0.016790137690866104 hrs\n",

      "[[57, 124, 272]]\n",

      "1775    8.724\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 56 with actual coord [57, 124, 272]\n",

      "Nodule Detected at slice# 57 with actual coord [57, 124, 272]\n",

      "Nodule Detected at slice# 58 with actual coord [57, 124, 272]\n",

      "Sensitivity: 0.44\n",

      "Specificity: 0.06666666666666667\n",

      "Processing patient# 209 ETA: -0.01980438633398579 hrs\n",

      "Processing patient# 210 ETA: -0.021900115047813088 hrs\n",

      "[[32, 157, 161], [46, 175, 381]]\n",

      "1776     5.381\n",

      "1777    11.452\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.4074074074074074\n",

      "Specificity: 0.06521739130434782\n",

      "Processing patient# 211 ETA: -0.02493481744553555 hrs\n",

      "[[181, 396, 260]]\n",

      "1778    16.014\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.39285714285714285\n",

      "Specificity: 0.06066176470588235\n",

      "Processing patient# 212 ETA: -0.03144206567755292 hrs\n",

      "[[119, 388, 303], [135, 356, 364], [127, 383, 316]]\n",

      "1779    11.814\n",

      "1780     8.744\n",

      "1781     7.308\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 118 with actual coord [119, 388, 303]\n",

      "Nodule Detected at slice# 119 with actual coord [119, 388, 303]\n",

      "Nodule Detected at slice# 120 with actual coord [119, 388, 303]\n",

      "Nodule Detected at slice# 134 with actual coord [135, 356, 364]\n",

      "Nodule Detected at slice# 135 with actual coord [135, 356, 364]\n",

      "Nodule Detected at slice# 136 with actual coord [135, 356, 364]\n",

      "Sensitivity: 0.41935483870967744\n",

      "Specificity: 0.06554621848739496\n",

      "Processing patient# 213 ETA: -0.03726589909150814 hrs\n",

      "Processing patient# 214 ETA: -0.03994502615334467 hrs\n",

      "[[350, 426, 351]]\n",

      "1782    4.721\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.40625\n",

      "Specificity: 0.060842433697347896\n",

      "Processing patient# 215 ETA: -0.04846682252809981 hrs\n",

      "Processing patient# 216 ETA: -0.051458642850687464 hrs\n",

      "[[28, 363, 267], [149, 175, 173], [42, 398, 263], [85, 97, 255], [160, 324, 326], [28, 378, 301], [84, 189, 340], [112, 385, 189], [55, 120, 325], [39, 143, 282], [139, 115, 364], [22, 168, 275], [97, 181, 189], [54, 144, 243], [43, 184, 250], [95, 378, 267], [88, 380, 242], [59, 372, 279], [104, 143, 204], [45, 173, 202], [117, 345, 203]]\n",

      "1783     3.424\n",

      "1784     3.490\n",

      "1785     6.809\n",

      "1786     9.657\n",

      "1787     7.511\n",

      "1788     3.424\n",

      "1789     4.754\n",

      "1790     6.805\n",

      "1791     5.048\n",

      "1792     6.979\n",

      "1793     6.282\n",

      "1794     8.001\n",

      "1795     3.584\n",

      "1796     4.227\n",

      "1797     7.514\n",

      "1798     6.351\n",

      "1799     6.649\n",

      "1800    10.118\n",

      "1801     6.016\n",

      "1802     6.732\n",

      "1803     5.577\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 85 with actual coord [85, 97, 255]\n",

      "Nodule Detected at slice# 86 with actual coord [85, 97, 255]\n",

      "Nodule Detected at slice# 160 with actual coord [160, 324, 326]\n",

      "Nodule Detected at slice# 161 with actual coord [160, 324, 326]\n",

      "Nodule Detected at slice# 138 with actual coord [139, 115, 364]\n",

      "Nodule Detected at slice# 139 with actual coord [139, 115, 364]\n",

      "Nodule Detected at slice# 140 with actual coord [139, 115, 364]\n",

      "Nodule Detected at slice# 103 with actual coord [104, 143, 204]\n",

      "Nodule Detected at slice# 104 with actual coord [104, 143, 204]\n",

      "Nodule Detected at slice# 105 with actual coord [104, 143, 204]\n",

      "Nodule Detected at slice# 44 with actual coord [45, 173, 202]\n",

      "Nodule Detected at slice# 45 with actual coord [45, 173, 202]\n",

      "Nodule Detected at slice# 46 with actual coord [45, 173, 202]\n",

      "Sensitivity: 0.33962264150943394\n",

      "Specificity: 0.07547169811320754\n",

      "Processing patient# 217 ETA: -0.057393515692633755 hrs\n",

      "[[55, 165, 400], [73, 90, 290], [48, 320, 382], [52, 309, 375], [27, 316, 165], [85, 99, 357], [63, 159, 399], [77, 307, 363]]\n",

      "1804    3.614\n",

      "1805    3.841\n",

      "1806    5.326\n",

      "1807    4.183\n",

      "1808    3.994\n",

      "1809    4.437\n",

      "1810    4.477\n",

      "1811    5.725\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 77 with actual coord [77, 307, 363]\n",

      "Sensitivity: 0.3114754098360656\n",

      "Specificity: 0.07604017216642754\n",

      "Processing patient# 218 ETA: -0.062303517685023985 hrs\n",

      "[[259, 172, 189], [269, 167, 247], [281, 36, 284]]\n",

      "1812    13.978\n",

      "1813     8.797\n",

      "1814     3.630\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 258 with actual coord [259, 172, 189]\n",

      "Nodule Detected at slice# 259 with actual coord [259, 172, 189]\n",

      "Nodule Detected at slice# 260 with actual coord [259, 172, 189]\n",

      "Nodule Detected at slice# 268 with actual coord [269, 167, 247]\n",

      "Nodule Detected at slice# 269 with actual coord [269, 167, 247]\n",

      "Nodule Detected at slice# 270 with actual coord [269, 167, 247]\n"

     ]

    },

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Sensitivity: 0.328125\n",

      "Specificity: 0.07554417413572344\n",

      "Processing patient# 219 ETA: -0.07084722954811999 hrs\n",

      "Processing patient# 220 ETA: -0.07423709965113441 hrs\n",

      "Processing patient# 221 ETA: -0.07759629722454255 hrs\n",

      "Processing patient# 222 ETA: -0.08092523676855068 hrs\n",

      "[[106, 436, 345]]\n",

      "1815    5.017\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 105 with actual coord [106, 436, 345]\n",

      "Nodule Detected at slice# 106 with actual coord [106, 436, 345]\n",

      "Sensitivity: 0.3384615384615385\n",

      "Specificity: 0.07682619647355164\n",

      "Processing patient# 223 ETA: -0.08694170671045097 hrs\n",

      "[[80, 427, 210]]\n",

      "1816    4.721\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.3333333333333333\n",

      "Specificity: 0.07634543178973717\n",

      "Processing patient# 224 ETA: -0.0926084516587711 hrs\n",

      "[[39, 211, 267]]\n",

      "1817    7.124\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.3283582089552239\n",

      "Specificity: 0.07530864197530865\n",

      "Processing patient# 225 ETA: -0.09882077568107181 hrs\n",

      "[[106, 150, 259], [51, 196, 303]]\n",

      "1818    6.787\n",

      "1819    4.547\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.3188405797101449\n",

      "Specificity: 0.07340553549939831\n",

      "Processing patient# 226 ETA: -0.10466439107760796 hrs\n",

      "[[112, 370, 208]]\n",

      "1820    3.587\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.3142857142857143\n",

      "Specificity: 0.06725468577728776\n",

      "Processing patient# 227 ETA: -0.11528374142583768 hrs\n",

      "[[37, 330, 191]]\n",

      "1821    28.0\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 36 with actual coord [37, 330, 191]\n",

      "Nodule Detected at slice# 37 with actual coord [37, 330, 191]\n",

      "Nodule Detected at slice# 38 with actual coord [37, 330, 191]\n",

      "Sensitivity: 0.323943661971831\n",

      "Specificity: 0.06823027718550106\n",

      "Processing patient# 228 ETA: -0.12483760813988208 hrs\n",

      "[[128, 149, 305], [138, 251, 277]]\n",

      "1822    15.151\n",

      "1823    10.452\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 127 with actual coord [128, 149, 305]\n",

      "Nodule Detected at slice# 128 with actual coord [128, 149, 305]\n",

      "Nodule Detected at slice# 129 with actual coord [128, 149, 305]\n",

      "Nodule Detected at slice# 137 with actual coord [138, 251, 277]\n",

      "Nodule Detected at slice# 138 with actual coord [138, 251, 277]\n",

      "Nodule Detected at slice# 139 with actual coord [138, 251, 277]\n",

      "Sensitivity: 0.3424657534246575\n",

      "Specificity: 0.06272401433691756\n",

      "Processing patient# 229 ETA: -0.13718350996009815 hrs\n",

      "[[96, 365, 149]]\n",

      "1824    5.333\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 95 with actual coord [96, 365, 149]\n",

      "Nodule Detected at slice# 96 with actual coord [96, 365, 149]\n",

      "Nodule Detected at slice# 97 with actual coord [96, 365, 149]\n",

      "Sensitivity: 0.35135135135135137\n",

      "Specificity: 0.0634231103388358\n",

      "Processing patient# 230 ETA: -0.14709678301776674 hrs\n",

      "[[213, 148, 384]]\n",

      "1825    5.994\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 212 with actual coord [213, 148, 384]\n",

      "Nodule Detected at slice# 213 with actual coord [213, 148, 384]\n",

      "Nodule Detected at slice# 214 with actual coord [213, 148, 384]\n",

      "Sensitivity: 0.36\n",

      "Specificity: 0.062193126022913256\n",

      "Processing patient# 231 ETA: -0.161781463566854 hrs\n",

      "[[14, 336, 324], [79, 290, 379], [29, 353, 260], [61, 209, 313], [121, 107, 374], [16, 350, 331]]\n",

      "1826     4.367\n",

      "1827     3.951\n",

      "1828    14.283\n",

      "1829     6.438\n",

      "1830     2.490\n",

      "1831     5.967\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 28 with actual coord [29, 353, 260]\n",

      "Nodule Detected at slice# 29 with actual coord [29, 353, 260]\n",

      "Nodule Detected at slice# 15 with actual coord [16, 350, 331]\n",

      "Nodule Detected at slice# 16 with actual coord [16, 350, 331]\n",

      "Nodule Detected at slice# 17 with actual coord [16, 350, 331]\n",

      "Sensitivity: 0.35802469135802467\n",

      "Specificity: 0.06398104265402843\n",

      "Processing patient# 232 ETA: -0.17268129442843436 hrs\n",

      "[[91, 110, 254], [179, 382, 210], [40, 286, 270], [245, 108, 331], [78, 163, 283], [86, 142, 306], [291, 350, 309], [51, 325, 235]]\n",

      "1832     5.025\n",

      "1833     4.149\n",

      "1834     5.928\n",

      "1835    14.410\n",

      "1836     5.033\n",

      "1837    24.621\n",

      "1838     6.646\n",

      "1839     3.814\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 90 with actual coord [91, 110, 254]\n",

      "Nodule Detected at slice# 91 with actual coord [91, 110, 254]\n",

      "Nodule Detected at slice# 92 with actual coord [91, 110, 254]\n",

      "Nodule Detected at slice# 244 with actual coord [245, 108, 331]\n",

      "Nodule Detected at slice# 245 with actual coord [245, 108, 331]\n",

      "Nodule Detected at slice# 246 with actual coord [245, 108, 331]\n",

      "Nodule Detected at slice# 85 with actual coord [86, 142, 306]\n",

      "Nodule Detected at slice# 86 with actual coord [86, 142, 306]\n",

      "Nodule Detected at slice# 87 with actual coord [86, 142, 306]\n",

      "Sensitivity: 0.3595505617977528\n",

      "Specificity: 0.06540697674418605\n",

      "Processing patient# 233 ETA: -0.18614303947688857 hrs\n",

      "[[132, 133, 372], [88, 369, 344], [169, 58, 317]]\n",

      "1840    21.897\n",

      "1841     4.149\n",

      "1842     6.785\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 131 with actual coord [132, 133, 372]\n",

      "Nodule Detected at slice# 132 with actual coord [132, 133, 372]\n",

      "Nodule Detected at slice# 133 with actual coord [132, 133, 372]\n",

      "Nodule Detected at slice# 168 with actual coord [169, 58, 317]\n",

      "Nodule Detected at slice# 169 with actual coord [169, 58, 317]\n",

      "Nodule Detected at slice# 170 with actual coord [169, 58, 317]\n",

      "Sensitivity: 0.3695652173913043\n",

      "Specificity: 0.06486486486486487\n",

      "Processing patient# 234 ETA: -0.19722831309577563 hrs\n",

      "[[172, 380, 269], [244, 358, 324]]\n",

      "1843    6.131\n",

      "1844    4.974\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.3617021276595745\n",

      "Specificity: 0.06319947333772219\n",

      "Processing patient# 235 ETA: -0.2140280986748126 hrs\n",

      "[[350, 475, 257], [234, 72, 263], [384, 440, 309]]\n",

      "1845     6.637\n",

      "1846     4.979\n",

      "1847    10.978\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 349 with actual coord [350, 475, 257]\n",

      "Nodule Detected at slice# 350 with actual coord [350, 475, 257]\n",

      "Nodule Detected at slice# 351 with actual coord [350, 475, 257]\n",

      "Nodule Detected at slice# 383 with actual coord [384, 440, 309]\n",

      "Nodule Detected at slice# 384 with actual coord [384, 440, 309]\n",

      "Nodule Detected at slice# 385 with actual coord [384, 440, 309]\n",

      "Sensitivity: 0.3711340206185567\n",

      "Specificity: 0.06386975579211021\n",

      "Processing patient# 236 ETA: -0.2297073334152416 hrs\n",

      "[[42, 127, 267]]\n",

      "1848    12.49\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 42 with actual coord [42, 127, 267]\n",

      "Nodule Detected at slice# 43 with actual coord [42, 127, 267]\n",

      "Sensitivity: 0.37755102040816324\n",

      "Specificity: 0.06463642013673089\n",

      "Processing patient# 237 ETA: -0.2382809225978061 hrs\n",

      "[[35, 183, 313], [32, 168, 249], [31, 188, 278], [46, 365, 303], [32, 178, 254], [66, 88, 347], [67, 387, 238]]\n",

      "1849     5.745\n",

      "1850     6.894\n",

      "1851    10.471\n",

      "1852     7.121\n",

      "1853     5.399\n",

      "1854     4.860\n",

      "1855     4.214\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 31 with actual coord [32, 168, 249]\n",

      "Nodule Detected at slice# 30 with actual coord [31, 188, 278]\n",

      "Nodule Detected at slice# 46 with actual coord [46, 365, 303]\n",

      "Nodule Detected at slice# 31 with actual coord [32, 178, 254]\n",

      "Sensitivity: 0.3904761904761905\n",

      "Specificity: 0.06572481572481573\n",

      "Processing patient# 238 ETA: -0.24610479066852778 hrs\n",

      "[[33, 123, 298], [45, 395, 224]]\n",

      "1856     5.051\n",

      "1857    20.840\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 33 with actual coord [33, 123, 298]\n",

      "Nodule Detected at slice# 34 with actual coord [33, 123, 298]\n",

      "Nodule Detected at slice# 44 with actual coord [45, 395, 224]\n",

      "Nodule Detected at slice# 45 with actual coord [45, 395, 224]\n",

      "Nodule Detected at slice# 46 with actual coord [45, 395, 224]\n",

      "Sensitivity: 0.40186915887850466\n",

      "Specificity: 0.06694560669456066\n",

      "Processing patient# 239 ETA: -0.25461648094188555 hrs\n",

      "[[26, 450, 295], [29, 134, 162], [17, 154, 186], [9, 186, 233], [7, 357, 271], [40, 431, 176]]\n",

      "1858     8.822\n",

      "1859    20.158\n",

      "1860     5.278\n",

      "1861     4.879\n",

      "1862     5.836\n",

      "1863     4.157\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 25 with actual coord [26, 450, 295]\n",

      "Nodule Detected at slice# 26 with actual coord [26, 450, 295]\n",

      "Nodule Detected at slice# 27 with actual coord [26, 450, 295]\n",

      "Nodule Detected at slice# 28 with actual coord [29, 134, 162]\n",

      "Nodule Detected at slice# 29 with actual coord [29, 134, 162]\n",

      "Nodule Detected at slice# 30 with actual coord [29, 134, 162]\n",

      "Nodule Detected at slice# 16 with actual coord [17, 154, 186]\n",

      "Nodule Detected at slice# 17 with actual coord [17, 154, 186]\n"

     ]

    },

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Nodule Detected at slice# 6 with actual coord [7, 357, 271]\n",

      "Nodule Detected at slice# 7 with actual coord [7, 357, 271]\n",

      "Sensitivity: 0.415929203539823\n",

      "Specificity: 0.07072463768115941\n",

      "Processing patient# 240 ETA: -0.26243001013994216 hrs\n",

      "Processing patient# 241 ETA: -0.2678747106774603 hrs\n",

      "Processing patient# 242 ETA: -0.27327441828145815 hrs\n",

      "[[152, 452, 272], [126, 462, 244]]\n",

      "1864    7.844\n",

      "1865    5.099\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 151 with actual coord [152, 452, 272]\n",

      "Nodule Detected at slice# 152 with actual coord [152, 452, 272]\n",

      "Nodule Detected at slice# 153 with actual coord [152, 452, 272]\n",

      "Nodule Detected at slice# 126 with actual coord [126, 462, 244]\n",

      "Sensitivity: 0.4260869565217391\n",

      "Specificity: 0.07167235494880546\n",

      "Processing patient# 243 ETA: -0.28365627678769567 hrs\n",

      "[[57, 155, 175], [79, 410, 341], [55, 124, 317], [74, 90, 315], [20, 157, 383], [82, 57, 381], [58, 167, 157]]\n",

      "1866     5.817\n",

      "1867     5.940\n",

      "1868     6.173\n",

      "1869     5.216\n",

      "1870    23.636\n",

      "1871     4.597\n",

      "1872     8.153\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 56 with actual coord [57, 155, 175]\n",

      "Nodule Detected at slice# 57 with actual coord [57, 155, 175]\n",

      "Nodule Detected at slice# 79 with actual coord [79, 410, 341]\n",

      "Nodule Detected at slice# 74 with actual coord [74, 90, 315]\n",

      "Nodule Detected at slice# 19 with actual coord [20, 157, 383]\n",

      "Nodule Detected at slice# 20 with actual coord [20, 157, 383]\n",

      "Nodule Detected at slice# 21 with actual coord [20, 157, 383]\n",

      "Nodule Detected at slice# 58 with actual coord [58, 167, 157]\n",

      "Sensitivity: 0.4426229508196721\n",

      "Specificity: 0.07481853713009493\n",

      "Processing patient# 244 ETA: -0.2921640377824206 hrs\n",

      "[[95, 147, 399]]\n",

      "1873    11.987\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 94 with actual coord [95, 147, 399]\n",

      "Nodule Detected at slice# 95 with actual coord [95, 147, 399]\n",

      "Nodule Detected at slice# 96 with actual coord [95, 147, 399]\n",

      "Sensitivity: 0.44715447154471544\n",

      "Specificity: 0.07523338824821527\n",

      "Processing patient# 245 ETA: -0.30634670570188643 hrs\n",

      "[[41, 309, 334]]\n",

      "1874    16.965\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 40 with actual coord [41, 309, 334]\n",

      "Nodule Detected at slice# 41 with actual coord [41, 309, 334]\n",

      "Nodule Detected at slice# 42 with actual coord [41, 309, 334]\n",

      "Sensitivity: 0.45161290322580644\n",

      "Specificity: 0.07246376811594203\n",

      "Processing patient# 246 ETA: -0.3249079197058293 hrs\n",

      "Processing patient# 247 ETA: -0.3306272812410887 hrs\n",

      "[[206, 407, 292], [134, 248, 153], [79, 95, 255]]\n",

      "1875    6.654\n",

      "1876    2.453\n",

      "1877    2.576\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.4409448818897638\n",

      "Specificity: 0.07045797684952189\n",

      "Processing patient# 248 ETA: -0.3484334776350248 hrs\n",

      "Processing patient# 249 ETA: -0.35426413378083554 hrs\n",

      "[[29, 217, 370]]\n",

      "1878    11.947\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 28 with actual coord [29, 217, 370]\n",

      "Nodule Detected at slice# 29 with actual coord [29, 217, 370]\n",

      "Nodule Detected at slice# 30 with actual coord [29, 217, 370]\n",

      "Sensitivity: 0.4453125\n",

      "Specificity: 0.0715\n",

      "Processing patient# 250 ETA: -0.36293431421120964 hrs\n",

      "[[142, 400, 372], [131, 168, 245], [144, 118, 327]]\n",

      "1879    4.377\n",

      "1880    4.689\n",

      "1881    9.531\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 143 with actual coord [144, 118, 327]\n",

      "Nodule Detected at slice# 144 with actual coord [144, 118, 327]\n",

      "Nodule Detected at slice# 145 with actual coord [144, 118, 327]\n",

      "Sensitivity: 0.44274809160305345\n",

      "Specificity: 0.07070217917675545\n",

      "Processing patient# 251 ETA: -0.3774032429292066 hrs\n",

      "[[65, 85, 316], [32, 389, 266], [36, 74, 286], [43, 306, 289]]\n",

      "1882    5.032\n",

      "1883    4.637\n",

      "1884    4.315\n",

      "1885    4.920\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.42962962962962964\n",

      "Specificity: 0.07049734427812651\n",

      "Processing patient# 252 ETA: -0.3872358038248841 hrs\n",

      "[[373, 110, 213], [310, 424, 247], [278, 399, 266]]\n",

      "1886    8.427\n",

      "1887    6.451\n",

      "1888    7.986\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 372 with actual coord [373, 110, 213]\n",

      "Nodule Detected at slice# 373 with actual coord [373, 110, 213]\n",

      "Nodule Detected at slice# 374 with actual coord [373, 110, 213]\n",

      "Nodule Detected at slice# 309 with actual coord [310, 424, 247]\n",

      "Nodule Detected at slice# 310 with actual coord [310, 424, 247]\n",

      "Nodule Detected at slice# 311 with actual coord [310, 424, 247]\n",

      "Nodule Detected at slice# 277 with actual coord [278, 399, 266]\n",

      "Nodule Detected at slice# 278 with actual coord [278, 399, 266]\n",

      "Nodule Detected at slice# 279 with actual coord [278, 399, 266]\n",

      "Sensitivity: 0.4420289855072464\n",

      "Specificity: 0.07119889756545705\n",

      "Processing patient# 253 ETA: -0.4086072258510558 hrs\n",

      "[[169, 441, 370]]\n",

      "1889    5.802\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 168 with actual coord [169, 441, 370]\n",

      "Nodule Detected at slice# 169 with actual coord [169, 441, 370]\n",

      "Nodule Detected at slice# 170 with actual coord [169, 441, 370]\n",

      "Sensitivity: 0.4460431654676259\n",

      "Specificity: 0.07165532879818594\n",

      "Processing patient# 254 ETA: -0.42418794325956216 hrs\n",

      "[[61, 396, 213], [53, 357, 225], [45, 409, 278], [51, 348, 238]]\n",

      "1890    6.900\n",

      "1891    5.399\n",

      "1892    7.599\n",

      "1893    3.894\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 60 with actual coord [61, 396, 213]\n",

      "Nodule Detected at slice# 61 with actual coord [61, 396, 213]\n",

      "Nodule Detected at slice# 62 with actual coord [61, 396, 213]\n",

      "Nodule Detected at slice# 44 with actual coord [45, 409, 278]\n",

      "Nodule Detected at slice# 45 with actual coord [45, 409, 278]\n",

      "Nodule Detected at slice# 46 with actual coord [45, 409, 278]\n",

      "Sensitivity: 0.44755244755244755\n",

      "Specificity: 0.07337807606263982\n",

      "Processing patient# 255 ETA: -0.43417470265577573 hrs\n",

      "[[29, 298, 336]]\n",

      "1894    5.354\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 28 with actual coord [29, 298, 336]\n",

      "Nodule Detected at slice# 29 with actual coord [29, 298, 336]\n",

      "Nodule Detected at slice# 30 with actual coord [29, 298, 336]\n",

      "Sensitivity: 0.4513888888888889\n",

      "Specificity: 0.07314936487078405\n",

      "Processing patient# 256 ETA: -0.44891197837889196 hrs\n",

      "[[220, 165, 295], [262, 449, 337]]\n",

      "1895    5.924\n",

      "1896    3.627\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 219 with actual coord [220, 165, 295]\n",

      "Nodule Detected at slice# 220 with actual coord [220, 165, 295]\n",

      "Nodule Detected at slice# 221 with actual coord [220, 165, 295]\n",

      "Sensitivity: 0.4520547945205479\n",

      "Specificity: 0.07333908541846419\n",

      "Processing patient# 257 ETA: -0.46991474398611116 hrs\n",

      "[[228, 397, 145], [146, 171, 371]]\n",

      "1897    3.963\n",

      "1898    3.407\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.44594594594594594\n",

      "Specificity: 0.07258753202391119\n",

      "Processing patient# 258 ETA: -0.4950783620837635 hrs\n",

      "[[308, 445, 204]]\n",

      "1899    4.872\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.4429530201342282\n",

      "Specificity: 0.07142857142857142\n",

      "Processing patient# 259 ETA: -0.5192839302087433 hrs\n",

      "[[162, 384, 276]]\n",

      "1900    3.868\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.44\n",

      "Specificity: 0.07036423841059603\n",

      "Processing patient# 260 ETA: -0.5385499058472806 hrs\n",

      "[[59, 379, 358]]\n",

      "1901    4.584\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.4370860927152318\n",

      "Specificity: 0.06967213114754098\n",

      "Processing patient# 261 ETA: -0.5554398855555559 hrs\n",

      "Processing patient# 262 ETA: -0.5623908352690091 hrs\n",

      "[[37, 162, 308], [99, 438, 231]]\n",

      "1902    11.949\n",

      "1903     5.186\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 36 with actual coord [37, 162, 308]\n",

      "Nodule Detected at slice# 37 with actual coord [37, 162, 308]\n",

      "Nodule Detected at slice# 38 with actual coord [37, 162, 308]\n",

      "Sensitivity: 0.43790849673202614\n",

      "Specificity: 0.07006885378695828\n",

      "Processing patient# 263 ETA: -0.5751002607690063 hrs\n",

      "[[163, 75, 267], [335, 135, 344], [253, 100, 149], [312, 351, 404], [338, 471, 310], [226, 156, 170], [232, 210, 405]]\n",

      "1904    3.448\n",

      "1905    5.672\n",

      "1906    4.273\n",

      "1907    4.199\n",

      "1908    5.043\n",

      "1909    3.188\n",

      "1910    6.405\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 334 with actual coord [335, 135, 344]\n",

      "Nodule Detected at slice# 335 with actual coord [335, 135, 344]\n",

      "Nodule Detected at slice# 336 with actual coord [335, 135, 344]\n",

      "Nodule Detected at slice# 337 with actual coord [338, 471, 310]\n",

      "Nodule Detected at slice# 338 with actual coord [338, 471, 310]\n",

      "Nodule Detected at slice# 339 with actual coord [338, 471, 310]\n"

     ]

    },

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Nodule Detected at slice# 231 with actual coord [232, 210, 405]\n",

      "Nodule Detected at slice# 232 with actual coord [232, 210, 405]\n",

      "Nodule Detected at slice# 233 with actual coord [232, 210, 405]\n",

      "Sensitivity: 0.4375\n",

      "Specificity: 0.07162534435261708\n",

      "Processing patient# 264 ETA: -0.6026041639533507 hrs\n",

      "[[321, 429, 151]]\n",

      "1911    8.894\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 320 with actual coord [321, 429, 151]\n",

      "Nodule Detected at slice# 321 with actual coord [321, 429, 151]\n",

      "Nodule Detected at slice# 322 with actual coord [321, 429, 151]\n",

      "Sensitivity: 0.4409937888198758\n",

      "Specificity: 0.07039573820395738\n",

      "Processing patient# 265 ETA: -0.6264781700302721 hrs\n",

      "[[51, 114, 331], [145, 90, 135], [49, 343, 368]]\n",

      "1912    4.010\n",

      "1913    3.234\n",

      "1914    3.756\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.4329268292682927\n",

      "Specificity: 0.06902985074626866\n",

      "Processing patient# 266 ETA: -0.6445316896641763 hrs\n",

      "[[129, 67, 312]]\n",

      "1915    4.118\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.4303030303030303\n",

      "Specificity: 0.06856931060044477\n",

      "Processing patient# 267 ETA: -0.6622083838423539 hrs\n",

      "Processing patient# 268 ETA: -0.6695844257223861 hrs\n",

      "Processing patient# 269 ETA: -0.6769056312730618 hrs\n",

      "[[280, 337, 359]]\n",

      "1916    4.285\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.42771084337349397\n",

      "Specificity: 0.06739526411657559\n",

      "Processing patient# 270 ETA: -0.7057049627706347 hrs\n",

      "[[35, 409, 203], [90, 128, 357], [44, 122, 235]]\n",

      "1917    3.412\n",

      "1918    7.682\n",

      "1919    4.133\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 89 with actual coord [90, 128, 357]\n",

      "Nodule Detected at slice# 90 with actual coord [90, 128, 357]\n",

      "Nodule Detected at slice# 91 with actual coord [90, 128, 357]\n",

      "Sensitivity: 0.4260355029585799\n",

      "Specificity: 0.06716684530189353\n",

      "Processing patient# 271 ETA: -0.72050155677161 hrs\n",

      "[[98, 140, 243], [111, 393, 370], [93, 336, 318], [106, 348, 382], [126, 187, 387], [102, 174, 245], [89, 418, 237]]\n",

      "1920     5.952\n",

      "1921    12.418\n",

      "1922    11.200\n",

      "1923     6.977\n",

      "1924     5.036\n",

      "1925     7.364\n",

      "1926     4.567\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 110 with actual coord [111, 393, 370]\n",

      "Nodule Detected at slice# 111 with actual coord [111, 393, 370]\n",

      "Nodule Detected at slice# 112 with actual coord [111, 393, 370]\n",

      "Nodule Detected at slice# 105 with actual coord [106, 348, 382]\n",

      "Nodule Detected at slice# 106 with actual coord [106, 348, 382]\n",

      "Nodule Detected at slice# 107 with actual coord [106, 348, 382]\n",

      "Nodule Detected at slice# 125 with actual coord [126, 187, 387]\n",

      "Nodule Detected at slice# 126 with actual coord [126, 187, 387]\n",

      "Nodule Detected at slice# 127 with actual coord [126, 187, 387]\n",

      "Nodule Detected at slice# 101 with actual coord [102, 174, 245]\n",

      "Nodule Detected at slice# 102 with actual coord [102, 174, 245]\n",

      "Nodule Detected at slice# 103 with actual coord [102, 174, 245]\n",

      "Sensitivity: 0.4318181818181818\n",

      "Specificity: 0.0703977472720873\n",

      "Processing patient# 272 ETA: -0.7400207091079039 hrs\n",

      "[[121, 434, 296], [135, 354, 427], [50, 162, 353], [110, 407, 253], [85, 117, 279], [154, 101, 311], [153, 78, 305], [154, 80, 341], [207, 61, 329], [111, 228, 383], [131, 107, 318], [112, 88, 322], [193, 302, 421], [103, 118, 390]]\n",

      "1927    2.755\n",

      "1928    4.160\n",

      "1929    7.594\n",

      "1930    3.217\n",

      "1931    3.290\n",

      "1932    3.114\n",

      "1933    7.743\n",

      "1934    3.923\n",

      "1935    3.242\n",

      "1936    6.221\n",

      "1937    3.032\n",

      "1938    4.318\n",

      "1939    3.060\n",

      "1940    4.332\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 49 with actual coord [50, 162, 353]\n",

      "Nodule Detected at slice# 50 with actual coord [50, 162, 353]\n",

      "Nodule Detected at slice# 51 with actual coord [50, 162, 353]\n",

      "Nodule Detected at slice# 152 with actual coord [153, 78, 305]\n",

      "Nodule Detected at slice# 153 with actual coord [153, 78, 305]\n",

      "Nodule Detected at slice# 154 with actual coord [153, 78, 305]\n",

      "Nodule Detected at slice# 110 with actual coord [111, 228, 383]\n",

      "Nodule Detected at slice# 111 with actual coord [111, 228, 383]\n",

      "Nodule Detected at slice# 112 with actual coord [111, 228, 383]\n",

      "Sensitivity: 0.41578947368421054\n",

      "Specificity: 0.07113682777399591\n",

      "Processing patient# 273 ETA: -0.7593161481325347 hrs\n",

      "[[41, 188, 301], [31, 412, 301], [16, 176, 273]]\n",

      "1941    9.821\n",

      "1942    4.962\n",

      "1943    6.837\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 40 with actual coord [41, 188, 301]\n",

      "Nodule Detected at slice# 41 with actual coord [41, 188, 301]\n",

      "Nodule Detected at slice# 42 with actual coord [41, 188, 301]\n",

      "Nodule Detected at slice# 16 with actual coord [16, 176, 273]\n",

      "Sensitivity: 0.41968911917098445\n",

      "Specificity: 0.07174132704614349\n",

      "Processing patient# 274 ETA: -0.7746534864586344 hrs\n",

      "[[332, 104, 351], [100, 188, 395]]\n",

      "1944    6.323\n",

      "1945    4.640\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 331 with actual coord [332, 104, 351]\n",

      "Nodule Detected at slice# 332 with actual coord [332, 104, 351]\n",

      "Nodule Detected at slice# 333 with actual coord [332, 104, 351]\n",

      "Sensitivity: 0.4205128205128205\n",

      "Specificity: 0.07248322147651007\n",

      "Processing patient# 275 ETA: -0.8112788267207869 hrs\n",

      "Processing patient# 276 ETA: -0.8191174224954872 hrs\n",

      "Processing patient# 277 ETA: -0.8268994259042908 hrs\n",

      "[[54, 418, 175]]\n",

      "1946    5.393\n",

      "Name: eq. diam., dtype: float64\n",

      "Sensitivity: 0.41836734693877553\n",

      "Specificity: 0.07228915662650602\n",

      "Processing patient# 278 ETA: -0.8407219234544882 hrs\n",

      "[[104, 411, 303], [87, 98, 305], [25, 219, 260], [83, 417, 171], [81, 87, 186], [72, 116, 169], [73, 105, 154], [92, 99, 271]]\n",

      "1947    6.309\n",

      "1948    4.931\n",

      "1949    5.281\n",

      "1950    4.364\n",

      "1951    5.831\n",

      "1952    4.043\n",

      "1953    4.297\n",

      "1954    3.841\n",

      "Name: eq. diam., dtype: float64\n",

      "Nodule Detected at slice# 104 with actual coord [104, 411, 303]\n",

      "Nodule Detected at slice# 105 with actual coord [104, 411, 303]\n",

      "Nodule Detected at slice# 81 with actual coord [81, 87, 186]\n",

      "Sensitivity: 0.4117647058823529\n",

      "Specificity: 0.07275747508305648\n",

      "Processing patient# 279 ETA: -0.8547288398973403 hrs\n",

      "[[75, 398, 373], [60, 195, 294], [34, 183, 332], [58, 165, 214], [11, 212, 298], [72, 152, 148]]\n",

      "1955    10.394\n",

      "1956    14.815\n",

      "1957    15.618\n",

      "1958     6.461\n",

      "1959     6.971\n",