Datasets
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Downloads: 1
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import numpy as np\n",
"import pandas as pd\n",
"from scipy.misc.pilutil import imresize\n",
"from glob import glob\n",
"from utils import get_itk_array"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"nii_path = glob(r'./data_0614/*.nii.gz')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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" './data_0614\\\\2020035396_0211_Lung_Screening_20200211143300_203.nii.gz',\n",
" './data_0614\\\\2020035396_0213_Lung_Screening_20200213135411_201.nii.gz',\n",
" './data_0614\\\\2020035396_0213_Lung_Screening_20200213135411_203.nii.gz',\n",
" './data_0614\\\\2020035396_0216_Lung_Screening_20200216102811_201.nii.gz',\n",
" './data_0614\\\\2020035396_0216_Lung_Screening_20200216102811_203.nii.gz',\n",
" './data_0614\\\\2020035396_0303_Chest_Thorax_20200303150020_2.nii.gz',\n",
" './data_0614\\\\2020035396_0303_Chest_Thorax_20200303150020_4.nii.gz',\n",
" './data_0614\\\\2020035751_0214_3050_20200214220726_2.nii.gz',\n",
" './data_0614\\\\2020035751_0214_3050_20200214220726_4.nii.gz',\n",
" './data_0614\\\\2020035751_0217_3052_20200217104646_2.nii.gz',\n",
" './data_0614\\\\2020035751_0217_3052_20200217104646_4.nii.gz',\n",
" './data_0614\\\\2020035751_0223_3051_20200223103122_2.nii.gz',\n",
" './data_0614\\\\2020035751_0223_3051_20200223103122_4.nii.gz',\n",
" './data_0614\\\\2020035751_0227_3051_20200227095603_2.nii.gz',\n",
" './data_0614\\\\2020035751_0227_3051_20200227095603_4.nii.gz',\n",
" './data_0614\\\\2020035751_0304_3051_20200304150058_2.nii.gz',\n",
" './data_0614\\\\2020035751_0304_3051_20200304150058_4.nii.gz',\n",
" './data_0614\\\\2020035751_0319_Chest_Thorax_20200319105532_2.nii.gz',\n",
" './data_0614\\\\2020035751_0319_Chest_Thorax_20200319105532_4.nii.gz',\n",
" './data_0614\\\\2020035775_0215_3050_20200215221834_2.nii.gz',\n",
" './data_0614\\\\2020035775_0215_3050_20200215221834_4.nii.gz',\n",
" './data_0614\\\\2020035775_0218_Lung_Screening_20200218084514_201.nii.gz',\n",
" './data_0614\\\\2020035775_0218_Lung_Screening_20200218084514_203.nii.gz',\n",
" './data_0614\\\\2020035775_0221_3051_20200221131815_3.nii.gz',\n",
" './data_0614\\\\2020035775_0221_3051_20200221131815_5.nii.gz',\n",
" './data_0614\\\\2020035775_0224_3051_20200224092851_2.nii.gz',\n",
" './data_0614\\\\2020035775_0224_3051_20200224092851_4.nii.gz',\n",
" './data_0614\\\\2020035775_0302_3051_20200302133455_2.nii.gz',\n",
" './data_0614\\\\2020035775_0302_3051_20200302133455_4.nii.gz',\n",
" './data_0614\\\\2020035775_0313_Chest_Thorax_20200313093733_2.nii.gz',\n",
" './data_0614\\\\2020035775_0313_Chest_Thorax_20200313093733_4.nii.gz',\n",
" './data_0614\\\\2020035775_0327_Chest_Thorax_20200327091704_2.nii.gz',\n",
" './data_0614\\\\2020035775_0327_Chest_Thorax_20200327091704_4.nii.gz',\n",
" './data_0614\\\\2020036063_0222_3050_20200222144948_2.nii.gz',\n",
" './data_0614\\\\2020036063_0222_3050_20200222144948_4.nii.gz',\n",
" './data_0614\\\\2020036063_0225_3052_20200225103239_2.nii.gz',\n",
" './data_0614\\\\2020036063_0225_3052_20200225103239_4.nii.gz',\n",
" './data_0614\\\\2020036063_0229_3052_20200229105243_2.nii.gz',\n",
" './data_0614\\\\2020036063_0229_3052_20200229105243_4.nii.gz',\n",
" './data_0614\\\\2020036291_0226_3050_20200226235401_2.nii.gz',\n",
" './data_0614\\\\2020036291_0226_3050_20200226235401_4.nii.gz',\n",
" './data_0614\\\\2020036291_0229_3051_20200229104921_2.nii.gz',\n",
" './data_0614\\\\2020036291_0229_3051_20200229104921_4.nii.gz',\n",
" './data_0614\\\\2020036291_0304_3051_20200304145339_2.nii.gz',\n",
" './data_0614\\\\2020036291_0304_3051_20200304145339_4.nii.gz',\n",
" './data_0614\\\\2020036291_0312_Chest_Thorax_20200312104101_2.nii.gz',\n",
" './data_0614\\\\2020036291_0312_Chest_Thorax_20200312104101_4.nii.gz',\n",
" './data_0614\\\\2020036291_0326_Chest_Thorax_20200326095432_2.nii.gz',\n",
" './data_0614\\\\2020036291_0326_Chest_Thorax_20200326095432_4.nii.gz']"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nii_path"
]
},
{
"cell_type": "code",
"execution_count": 104,
"metadata": {},
"outputs": [],
"source": [
"test_path = nii_path[254:254+10]"
]
},
{
"cell_type": "code",
"execution_count": 105,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['./data_0614\\\\2020036291_0226_3050_20200226235401_2.nii.gz',\n",
" './data_0614\\\\2020036291_0226_3050_20200226235401_4.nii.gz',\n",
" './data_0614\\\\2020036291_0229_3051_20200229104921_2.nii.gz',\n",
" './data_0614\\\\2020036291_0229_3051_20200229104921_4.nii.gz',\n",
" './data_0614\\\\2020036291_0304_3051_20200304145339_2.nii.gz',\n",
" './data_0614\\\\2020036291_0304_3051_20200304145339_4.nii.gz',\n",
" './data_0614\\\\2020036291_0312_Chest_Thorax_20200312104101_2.nii.gz',\n",
" './data_0614\\\\2020036291_0312_Chest_Thorax_20200312104101_4.nii.gz',\n",
" './data_0614\\\\2020036291_0326_Chest_Thorax_20200326095432_2.nii.gz',\n",
" './data_0614\\\\2020036291_0326_Chest_Thorax_20200326095432_4.nii.gz']"
]
},
"execution_count": 105,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_path"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"matrix shape:\t (77, 512, 512)\n",
"matrix shape:\t (474, 512, 512)\n",
"matrix shape:\t (77, 512, 512)\n",
"matrix shape:\t (560, 512, 512)\n",
"matrix shape:\t (77, 512, 512)\n",
"matrix shape:\t (560, 512, 512)\n",
"matrix shape:\t (71, 512, 512)\n",
"matrix shape:\t (438, 512, 512)\n",
"matrix shape:\t (73, 512, 512)\n",
"matrix shape:\t (451, 512, 512)\n"
]
}
],
"source": [
"tag = 1\n",
"meta_data = []\n",
"for name in test_path:\n",
" nii, spacing = get_itk_array(name)\n",
" patientID = os.path.basename(name).split('.')[0].split('_')[0]\n",
" print('matrix shape:\\t', nii.shape)\n",
" nii[nii < -1000] = -1000\n",
" nii[nii > 512] = 512\n",
" nii = nii - np.min(nii)\n",
" nii = nii * 1.0 / np.max(nii)\n",
" if tag == 1:\n",
" total = nii\n",
" tag = 0\n",
" else:\n",
" total = np.concatenate((total, nii), axis=0)\n",
" meta_data.append({'patientID': patientID, 'filename': name, 'slice': nii.shape[0], 'spacing': spacing, 'shape': nii.shape})"
]
},
{
"cell_type": "code",
"execution_count": 107,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\hasee007\\AppData\\Roaming\\Python\\Python37\\site-packages\\ipykernel_launcher.py:4: DeprecationWarning: `imresize` is deprecated!\n",
"`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
"Use ``skimage.transform.resize`` instead.\n",
" after removing the cwd from sys.path.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"sacle of nii is changed after imresize!\n",
" Now, normlise:\n"
]
}
],
"source": [
"slices = total.shape[0]\n",
"total_all = np.zeros((slices, 256, 256)) # 初始化\n",
"for i in range(slices):\n",
" total_all[i, :, :] = imresize(total[i, :, :], (256, 256)) # 缩小尺寸\n",
"if np.max(total_all) > 1:\n",
" print('sacle of nii is changed after imresize!\\n Now, normlise:')\n",
" # normalise to 0-1\n",
" total_all = total_all - np.min(total_all)\n",
" total_all = total_all * 1.0 / np.max(total_all)"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"matrix shape:\t (2858, 256, 256)\n"
]
}
],
"source": [
"npy_name = name.split('\\\\')[-1].split('.')[0].split('_')[0]\n",
"np.save('{}.npy'.format(npy_name), total_all)\n",
"df = pd.DataFrame(meta_data)\n",
"df.to_csv('{}.csv'.format(npy_name))\n",
"print('matrix shape:\\t', total_all.shape) # (301, 512, 512)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}