{

 "cells": [

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "Let's load some sample dasets to test the code. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 102,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Downloading...\n",

      "From: https://drive.google.com/uc?id=1QZNgRojYpYBLzUQJntWAmw1QwQMh4H50\n",

      "To: /tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/datasets/sample_nifti_3D/patient101_frame14.nii.gz\n",

      "100%|████████████████████████████████████████| 667k/667k [00:00<00:00, 7.39MB/s]\n",

      "Downloading...\n",

      "From: https://drive.google.com/uc?id=1zFJM_qQKwz85xiYpX3XBRqhL0SQwy-Iw\n",

      "To: /tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/datasets/sample_nifti_3D/patient101_frame01.nii.gz\n",

      "100%|████████████████████████████████████████| 664k/664k [00:00<00:00, 3.10MB/s]\n",

      "Downloading...\n",

      "From: https://drive.google.com/uc?id=1FqTquCYhLD2-EKxmCR9A5zt5265AEPdQ\n",

      "To: /tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/datasets/sample_nifti_4D/patient101_4d.nii.gz\n",

      "20.0MB [00:01, 17.2MB/s]\n"

     ]

    }

   ],

   "source": [

    "!bash ./datasets/download_sample_dataset.sh"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "Load the pre-trained models that attached to the publication. This will download the cardiac segmentation and motion estimation trained parameters: "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 103,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Note: available models are carson_Jan2021, carmen_Jan2021\n",

      "Downloading models ...\n",

      "Downloading...\n",

      "From: https://drive.google.com/uc?id=1rINpNPZ4_lT9XuFB6Q7gyna_L4O3AIY9\n",

      "To: /tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/pretrained_models/carson_Jan2021.h5\n",

      "229MB [00:12, 18.6MB/s] \n",

      "Downloading...\n",

      "From: https://drive.google.com/uc?id=10eMGoYYa4xFdwFuiwC7bwVSJ6b-bx7Ni\n",

      "To: /tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/pretrained_models/carmen_Jan2021.h5\n",

      "449MB [00:23, 18.9MB/s] \n"

     ]

    }

   ],

   "source": [

    "!bash ./pretrained_models/download_model.sh"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "Test segmentation on 3D data in NIFTI format. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 104,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "+ DATAROOT=./datasets/sample_nifti_3D\n",

      "+ DATAFORMAT=NIFTI\n",

      "+ RESULTS_DIR=./results/sample_nifti_3D\n",

      "+ CARSON_PATH=../private_models/main_carson_model.h5\n",

      "+ CARMEN_PATH=./pretrained_models/carmen_Jan2021.h5\n",

      "+ PIPELINE=segmentation\n",

      "+ CUDA_VISIBLE_DEVICES=\n",

      "+ python ./test.py --dataroot ./datasets/sample_nifti_3D --dataformat NIFTI --results_dir ./results/sample_nifti_3D --pretrained_models_netS ../private_models/main_carson_model.h5 --pretrained_models_netME ./pretrained_models/carmen_Jan2021.h5 --pipeline segmentation\n",

      "2021-02-14 18:02:27.114286: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1\n",

      "2021-02-14 18:02:29.315607: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1\n",

      "2021-02-14 18:02:29.340591: E tensorflow/stream_executor/cuda/cuda_driver.cc:314] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n",

      "2021-02-14 18:02:29.340649: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: e990b504c5b4\n",

      "2021-02-14 18:02:29.340666: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: e990b504c5b4\n",

      "2021-02-14 18:02:29.340797: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 450.102.4\n",

      "2021-02-14 18:02:29.340843: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 450.102.4\n",

      "2021-02-14 18:02:29.340860: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:310] kernel version seems to match DSO: 450.102.4\n",

      "2021-02-14 18:02:29.341267: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",

      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",

      "2021-02-14 18:02:29.352981: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 1696155000 Hz\n",

      "2021-02-14 18:02:29.353521: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x4ad3bc0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",

      "2021-02-14 18:02:29.353563: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",

      "/tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/data/nifti_dataset.py:77: UserWarning: Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\n",

      "  warnings.warn(\"Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\")\n",

      "/tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/data/nifti_dataset.py:77: UserWarning: Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\n",

      "  warnings.warn(\"Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\")\n"

     ]

    }

   ],

   "source": [

    "!bash ./scripts/test_segmentation.sh ./datasets/sample_nifti_3D NIFTI ./results/sample_nifti_3D"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "Test segmentation on 4D (3D + time) data in NIFTI format. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 105,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "+ DATAROOT=./datasets/sample_nifti_4D\n",

      "+ DATAFORMAT=NIFTI\n",

      "+ RESULTS_DIR=./results/sample_nifti_4D\n",

      "+ CARSON_PATH=../private_models/main_carson_model.h5\n",

      "+ CARMEN_PATH=./pretrained_models/carmen_Jan2021.h5\n",

      "+ PIPELINE=segmentation\n",

      "+ CUDA_VISIBLE_DEVICES=\n",

      "+ python ./test.py --dataroot ./datasets/sample_nifti_4D --dataformat NIFTI --results_dir ./results/sample_nifti_4D --pretrained_models_netS ../private_models/main_carson_model.h5 --pretrained_models_netME ./pretrained_models/carmen_Jan2021.h5 --pipeline segmentation\n",

      "2021-02-14 18:02:36.541501: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1\n",

      "2021-02-14 18:02:38.748517: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1\n",

      "2021-02-14 18:02:38.772471: E tensorflow/stream_executor/cuda/cuda_driver.cc:314] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n",

      "2021-02-14 18:02:38.772523: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: e990b504c5b4\n",

      "2021-02-14 18:02:38.772544: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: e990b504c5b4\n",

      "2021-02-14 18:02:38.772684: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 450.102.4\n",

      "2021-02-14 18:02:38.772733: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 450.102.4\n",

      "2021-02-14 18:02:38.772749: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:310] kernel version seems to match DSO: 450.102.4\n",

      "2021-02-14 18:02:38.773126: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",

      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",

      "2021-02-14 18:02:38.784659: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 1696155000 Hz\n",

      "2021-02-14 18:02:38.785149: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x6260db0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",

      "2021-02-14 18:02:38.785202: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",

      "/tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/data/nifti_dataset.py:77: UserWarning: Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\n",

      "  warnings.warn(\"Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\")\n"

     ]

    }

   ],

   "source": [

    "!bash ./scripts/test_segmentation.sh ./datasets/sample_nifti_4D NIFTI ./results/sample_nifti_4D"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "Test motion on 4D (3D + time) data in NIFTI format. Motion is only avilable for 4D data. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 106,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "+ DATAROOT=./datasets/sample_nifti_4D\n",

      "+ DATAFORMAT=NIFTI\n",

      "+ RESULTS_DIR=./results/sample_nifti_4D\n",

      "+ CARSON_PATH=./pretrained_models/carson_Jan2021.h5\n",

      "+ CARMEN_PATH=./pretrained_models/carmen_Jan2021.h5\n",

      "+ PIPELINE=motion\n",

      "+ CUDA_VISIBLE_DEVICES=\n",

      "+ python ./test.py --dataroot ./datasets/sample_nifti_4D --dataformat NIFTI --results_dir ./results/sample_nifti_4D --pretrained_models_netS ./pretrained_models/carson_Jan2021.h5 --pretrained_models_netME ./pretrained_models/carmen_Jan2021.h5 --pipeline motion\n",

      "2021-02-14 18:03:25.301883: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1\n",

      "2021-02-14 18:03:27.512196: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1\n",

      "2021-02-14 18:03:27.536612: E tensorflow/stream_executor/cuda/cuda_driver.cc:314] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n",

      "2021-02-14 18:03:27.536661: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: e990b504c5b4\n",

      "2021-02-14 18:03:27.536678: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: e990b504c5b4\n",

      "2021-02-14 18:03:27.536807: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 450.102.4\n",

      "2021-02-14 18:03:27.536855: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 450.102.4\n",

      "2021-02-14 18:03:27.536872: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:310] kernel version seems to match DSO: 450.102.4\n",

      "2021-02-14 18:03:27.537213: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",

      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",

      "2021-02-14 18:03:27.549271: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 1696155000 Hz\n",

      "2021-02-14 18:03:27.549656: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x4af9c90 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",

      "2021-02-14 18:03:27.549686: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",

      "/tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/data/nifti_dataset.py:77: UserWarning: Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\n",

      "  warnings.warn(\"Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\")\n",

      "2021-02-14 18:03:38.911740: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:03:39.743555: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:03:40.195599: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:03:40.499049: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:03:41.084644: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n"

     ]

    }

   ],

   "source": [

    "!bash ./scripts/test_motion.sh ./datasets/sample_nifti_4D NIFTI ./results/sample_nifti_4D"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "Test both segmentation and motion on 4D niftis. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 107,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "+ DATAROOT=./datasets/sample_nifti_4D\n",

      "+ DATAFORMAT=NIFTI\n",

      "+ RESULTS_DIR=./results/sample_nifti_4D\n",

      "+ CARSON_PATH=./pretrained_models/carson_Jan2021.h5\n",

      "+ CARMEN_PATH=./pretrained_models/carmen_Jan2021.h5\n",

      "+ PIPELINE=segmentation_motion\n",

      "+ CUDA_VISIBLE_DEVICES=\n",

      "+ python ./test.py --dataroot ./datasets/sample_nifti_4D --dataformat NIFTI --results_dir ./results/sample_nifti_4D --pretrained_models_netS ./pretrained_models/carson_Jan2021.h5 --pretrained_models_netME ./pretrained_models/carmen_Jan2021.h5 --pipeline segmentation_motion\n",

      "2021-02-14 18:04:19.796322: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1\n",

      "2021-02-14 18:04:21.998095: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1\n",

      "2021-02-14 18:04:22.024630: E tensorflow/stream_executor/cuda/cuda_driver.cc:314] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n",

      "2021-02-14 18:04:22.024683: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: e990b504c5b4\n",

      "2021-02-14 18:04:22.024704: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: e990b504c5b4\n",

      "2021-02-14 18:04:22.024818: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 450.102.4\n",

      "2021-02-14 18:04:22.024863: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 450.102.4\n",

      "2021-02-14 18:04:22.024878: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:310] kernel version seems to match DSO: 450.102.4\n",

      "2021-02-14 18:04:22.025239: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",

      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",

      "2021-02-14 18:04:22.036833: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 1696155000 Hz\n",

      "2021-02-14 18:04:22.037295: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5482b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",

      "2021-02-14 18:04:22.037323: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",

      "/tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/data/nifti_dataset.py:77: UserWarning: Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\n",

      "  warnings.warn(\"Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\")\n",

      "/tf/Dropbox (Partners HealthCare)/ubuntu/docker/repos/DeepStrain/data/nifti_dataset.py:77: UserWarning: Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\n",

      "  warnings.warn(\"Affine in nifti might be set incorrectly. Setting to affine=affine*zooms\")\n",

      "2021-02-14 18:05:17.144698: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:05:17.945462: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:05:18.392550: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:05:18.698553: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n",

      "2021-02-14 18:05:19.246800: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 1946157056 exceeds 10% of free system memory.\n"

     ]

    }

   ],

   "source": [

    "!bash ./scripts/test_segmentation_motion.sh ./datasets/sample_nifti_4D NIFTI ./results/sample_nifti_4D"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "After the segmentations and motion estimates have been generated, we can use both calculate myocardial strain. Note that we're passing the output folder from the previous runs. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 108,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "+ RESULTS_DIR=./results/sample_nifti_4D\n",

      "+ PIPELINE=strain\n",

      "+ CUDA_VISIBLE_DEVICES=\n",

      "+ python ./test.py --dataroot ./results/sample_nifti_4D --results_dir ./results/sample_nifti_4D --pipeline strain\n",

      "2021-02-14 18:05:58.124863: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1\n",

      "0.0 0.0\n",

      "-0.0028643845930383114 1.082031278527137e-05\n",

      "0.050226276271155106 -0.08250821851016393\n",

      "0.0565662083407661 -0.08721526046380865\n",

      "0.06341052114161663 -0.09039004858265032\n",

      "0.062187569151276205 -0.09092932158690682\n",

      "0.06273986208445685 -0.09008545707566279\n",

      "0.06704142900754055 -0.09048872862980738\n",

      "0.06900019280843682 -0.09202953300260222\n",

      "0.06752667505148324 -0.09357088160323081\n",

      "0.062176541303209334 -0.09396584141478774\n",

      "0.05509482533956014 -0.09227094988109329\n",

      "-0.011429068055575722 -0.006970679116830844\n",

      "0.04503282824559175 -0.08830198004612085\n",

      "0.03627042423655744 -0.08262235528522073\n",

      "0.029786156419924492 -0.07606680680357371\n",

      "0.026712081007800637 -0.06975290381524307\n",

      "0.019263847211321777 -0.06391941641474\n",

      "0.007899134163335668 -0.055720237241491964\n",

      "-0.005480475496803074 -0.03917932457221275\n",

      "-0.00592674874319504 -0.010661710877623127\n",

      "-0.0024683947363135297 -0.0014360990600069954\n",

      "-0.0021524594363897293 5.030914597078318e-05\n",

      "-0.026725685733460826 -0.02099679369525766\n",

      "-0.02529592552751031 -0.03299636940750714\n",

      "-0.010376969736070649 -0.04378397382622917\n",

      "0.002002523134231003 -0.05443799860918108\n",

      "0.015893347546116793 -0.06210413845861033\n",

      "0.02648765196612738 -0.06909838143488618\n",

      "0.03835757750338634 -0.0751729741905356\n"

     ]

    }

   ],

   "source": [

    "!bash ./scripts/test_strain.sh ./results/sample_nifti_4D"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": null,

   "metadata": {},

   "outputs": [],

   "source": []

  },

  {

   "cell_type": "code",

   "execution_count": null,

   "metadata": {},

   "outputs": [],

   "source": []

  },

  {

   "cell_type": "code",

   "execution_count": null,

   "metadata": {},

   "outputs": [],

   "source": []

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