{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### MAIN NOTEBOOK DE ARMADO DE DATASET PARA SEGMENTACIÓN ÍNTEGRA -> CÁLCULO DE VOLUMEN (después de probar todo lo posible)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import nibabel as nib\n", "import numpy as np\n", "import cv2\n", "import torchio as tio\n", "import matplotlib.pyplot as plt\n", "import SimpleITK as sitk\n", "from PIL import Image\n", "import elasticdeform\n", "from sklearn.model_selection import train_test_split\n", "import shutil\n", "from nyul import nyul_train_standard_scale\n", "from nyul import nyul_apply_standard_scale" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### INFO GENERAL DEL DATASET\n", "\n", "Hay 6 datasets rejuntados -> total de 116 pacientes -> todas secuencias T2 con sus máscaras anexas en formato .nii
\n", "Todo los dataset tienen secuencias mixtas en tamaño de pixel y cantidad de slices.
\n", "Además, algunas tienen endorectal coil.
\n", "Aclaración: no se realizó ningun registro (centrado en base a imágen madre) ya que el dataset ya viene preprocesado en ese sentido.
\n", "\n", "#### PREPROCESADO\n", "\n", "A priori, se renombraron todos las secuencias y sus máscaras en un formato conveniente.
\n", "\n", "1. Se realizó un flip de 90° ya que las imágenes viniero rotadas. Además se binarizaron las máscaras ya que algunos datasets tenian multiclase.
\n", "\n", "2. Se aplicó Bias Correction (N4ITK) a todas las secuencias (incluidas las de TEST ya que se supone parte del preprocesado).
\n", "\n", "3. Se separaron los 116 pacientes en 10% test (12), del 90% restante (104), 75% train (77), 25% validation (27).
\n", ">* Se separó a nivel paciente siguiendo los criterios del \"Checklist for Artificial Intelligence in Medical Imaging\" (CLAIM).
\n", "\n", "4. Se normalizaron las secuencias utilizando el algoritmo de Nyul.
\n", ">* Del entrenamiento de Nyul (con img de train) surgen los landmarks para el preprocesado de futuras secuencias.
\n", "\n", "5. Se separaron los slices de todas las secuencias en archivos formato .npy.
\n", ">* Se recortó el centro de las imágenes llevandolas de 384x384 a 256x256.
\n", ">* Se estandarizaron las imágenes con z-score normalization utilizando la media y desviación estándar las imágenes recortadas.
\n", ">* media = 3.4506247419236113, var = 42.43344987315689
\n", "\n", "6. Se realizó Data Augmentation del set de training y validation.
\n", ">* Se aplicó Elastic Deformation 2D aleatoriamente al casi 50% (randint) de slices.
\n", ">* Se hizo 2D por que 3D generaba artefactos. Además se realizo a la imágen completa, para recortar los defectos de borde.
\n", ">* Se utilizó la librería elasticdeformation con sigma=5 y points=10
\n", "\n", "Al final del split la cantidad de imágenes por set quedó: train: 2665, validation: 826, test: 396
\n", "Total = 3887
\n", "Con augmentation quedó: train: 4003, validation: 1228, test: 396
\n", "Total = 5627
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "RENAME" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fp = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\nuevas\"\n", "fp2 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\nuevas2\"\n", "allfiles = os.listdir(fp)\n", "allfilesfinales = os.listdir(fp2)\n", "cont = int(len(allfilesfinales)/2)\n", "cont2 = int(len(allfilesfinales)/2)\n", "for file in sorted(allfiles):\n", " print(file)\n", " if (\"segmentation\" in file ) or (\"Segmentation\" in file): \n", " cont+=1\n", " os.rename(os.path.join(fp,file),os.path.join(fp2,\"segmentacion_\"+str(cont).zfill(3)+\".nii\"))\n", " else:\n", " cont2+=1\n", " os.rename(os.path.join(fp,file),os.path.join(fp2,\"sujeto_\"+str(cont2).zfill(3)+\".nii\"))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "FLIP Y BINARIZADO " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fp = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\nuevas2\"\n", "fp2 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\nuevas\"\n", "allfiles = os.listdir(fp)\n", "for file in sorted(allfiles):\n", " print(file)\n", " x = nib.load(os.path.join(fp,file))\n", " img = x.get_fdata()\n", " img = np.rot90(img,3)\n", " if \"segmentacion\" in file: img = np.any(img)\n", " nifti = nib.Nifti1Image(img, header = x.header, affine= x.affine)\n", " nib.save(nifti, os.path.join(fp2, file)) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "BIAS CORRECTION" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fp = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\aa\"\n", "fp2 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\flipped\"\n", "allfiles = os.listdir(fp)\n", "for file in sorted(allfiles):\n", " if \"sujeto\" in file:\n", " x = nib.load(os.path.join(fp,file))\n", " img = x.get_fdata()\n", " inputImage = sitk.ReadImage(os.path.join(fp,file))\n", " maskImage = sitk.OtsuThreshold(inputImage,0,1,200)\n", " inputImage = sitk.Cast(inputImage,sitk.sitkFloat32)\n", " corrector = sitk.N4BiasFieldCorrectionImageFilter()\n", " output = corrector.Execute(inputImage,maskImage)\n", " newimg = np.transpose(sitk.GetArrayViewFromImage(output))\n", " nifti = nib.Nifti1Image(newimg, header = x.header, affine= x.affine)\n", " nib.save(nifti, os.path.join(fp2, file)) \n", " else:\n", " shutil.copy2(os.path.join(fp,file), os.path.join(fp2,file))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "SPLIT TRAIN-VALIDATION-TEST" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "fp1 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\bias_corrected_sec\\sujetos\"\n", "fp2 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\bias_corrected_sec\\mascaras\"\n", "sujetos = os.listdir(fp1)\n", "segmentaciones = os.listdir(fp2)\n", "suj_train,suj_test,seg_train,seg_test = train_test_split(sujetos,segmentaciones,train_size=0.9,random_state=23) #random_state = 23" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "\n", "fp1 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\bias_corrected_sec\\sujetos\"\n", "fp0 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\bias_corrected_sec\\mascaras\"\n", "fp2 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujetos\"\n", "fp3 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\test_data\\sujetos\"\n", "fp4 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\mascaras\"\n", "fp5 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\test_data\\mascaras\"\n", "\n", "for file in suj_train:\n", " shutil.copy2(os.path.join(fp1,file), os.path.join(fp2,file))\n", "for file in suj_test:\n", " shutil.copy2(os.path.join(fp1,file), os.path.join(fp3,file))\n", "for file in seg_train:\n", " shutil.copy2(os.path.join(fp0,file), os.path.join(fp4,file))\n", "for file in seg_test:\n", " shutil.copy2(os.path.join(fp0,file), os.path.join(fp5,file))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "fp1 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujetos\"\n", "fp2 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\mascaras\"\n", "sujetos = os.listdir(fp1)\n", "segmentaciones = os.listdir(fp2)\n", "suj_train,suj_val,seg_train,seg_val = train_test_split(sujetos,segmentaciones,train_size=0.75,random_state=23) #random_state = 23" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "fp1 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujetos\"\n", "fp0 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\mascaras\"\n", "fp3 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\validation_data\\sujetos\"\n", "fp5 = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\validation_data\\mascaras\"\n", "\n", "for file in suj_val:\n", " shutil.move(os.path.join(fp1,file), os.path.join(fp3,file))\n", "for file in seg_val:\n", " shutil.move(os.path.join(fp0,file), os.path.join(fp5,file))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fp = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\ds_mezcla_segmentacion integra\\bias_corrected_sec\\mascaras\"\n", "allfiles = os.listdir(fp)\n", "allz = 0\n", "allnz = 0\n", "\n", "for file in allfiles:\n", " if \"segmentacion\" in file:\n", " x = nib.load(os.path.join(fp,file))\n", " x = x.get_fdata()\n", " for slice in range(np.size(x,2)):\n", " if not np.any(x[:,:,slice]): allz+=1\n", " else: allnz+=1\n", "\n", "print(allz,allnz) #2020 1867 -> 48% de máscaras tienen próstata" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1416 1249 53.13320825515947\n", "416 410 50.363196125908\n", "188 208 47.474747474747474\n" ] } ], "source": [ "fp0 = [r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\mascaras\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\validation_data\\mascaras\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\test_data\\mascaras\"]\n", "for fp in fp0:\n", " allfiles = os.listdir(fp)\n", " allz = 0\n", " allnz = 0\n", " for file in allfiles:\n", " if \"segmentacion\" in file:\n", " x = nib.load(os.path.join(fp,file))\n", " x = x.get_fdata()\n", " for slice in range(np.size(x,2)):\n", " if not np.any(x[:,:,slice]): allz+=1\n", " else: allnz+=1\n", " print(allz,allnz,allz/(allz+allnz)*100) #cantidad de mascaras SIN prostata / CON prostata / SIN en % -> aprox 50+/-3% (dataset balanceado)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "SEPARACION DE SLICES (formato .npy)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Se normalizó y estandarizó el dataset (training).\n", "\n", "Primero, se calcularon los landmarks de la normalización de histogramas Nyul para MRI.
\n", "El objetivo de Nyul es eliminar las discrepancias en brillo para los mismos tejidos en distintas secuencias debidas a la diferencia de resonadores.
\n", "De alguna forma simula una escala similar a la que se encuentra en CT.
" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "standard_path = 'nyul_landmarks.npy'" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_001.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_002.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_004.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_007.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_008.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_009.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_012.nii\n", "processing scan 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C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_108.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_109.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_110.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_111.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_112.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_114.nii\n", "processing scan C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujeto_115.nii\n" ] } ], "source": [ "DATA_DIR = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\"\n", "\n", "train_scans = []\n", "for file in os.listdir(DATA_DIR):\n", " path = os.path.join(DATA_DIR,file)\n", " if not os.path.isdir(path):\n", " if \"sujeto\" in file:\n", " train_scans.append(path)\n", "\n", "standard_scale, perc = nyul_train_standard_scale(train_scans)\n", "\n", "np.save(standard_path, [standard_scale, perc])" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "El siguiente paso es la z-normalization de todo el dataset (training).
\n", "Se obtienen la media y desviación estándar del conjunto y luego se aplica individualmente a cada imágen." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "fp = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\"\n", "todas = []\n", "for file in os.listdir(fp):\n", " path = os.path.join(fp,file)\n", " if not os.path.isdir(path):\n", " if \"sujeto\" in file:\n", " x = nib.load(path)\n", " x = x.get_fdata()\n", " x = nyul_apply_standard_scale(x, standard_path)\n", " for slice in range(np.size(x,2)):\n", " todas.append(x[63:319,63:319,slice])#(256,256)\n", "ds_hist = np.ravel(todas)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(174653440,) -105.35324697378185 1438.5698506254516 128.5606638621487\n", "-105.35324697378185 127.20468995920034\n", "3.469224631926393 42.501930251698305\n", "5.8424965928392e-16 0.9999999999999982\n" ] } ], "source": [ "print(ds_hist.shape,np.min(ds_hist),np.max(ds_hist),3*np.std(ds_hist))\n", "p1, p2 = np.percentile(ds_hist,0), np.percentile(ds_hist,99.8)\n", "print(p1,p2) #-107.75208459640474 128.45794968358558\n", "ds_hist_per = np.clip(ds_hist,p1,p2) #si menor a p1 -> p1, si mayor a p2 -> p2\n", "media, var = np.mean(ds_hist_per), np.std(ds_hist_per) #3.4506247419236113 42.43344987315689\n", "print(media,var)\n", "ds_hist_norm= (ds_hist_per-media)/var\n", "print(np.mean(ds_hist_norm),np.std(ds_hist_norm))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "pruebas sin percentile y clipping" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3.54715519304951 42.85355462071623\n", "-1.9040429020822806e-16 1.000000000000004\n" ] } ], "source": [ "media, var = np.mean(ds_hist), np.std(ds_hist) #3.54715519304951 42.85355462071623\n", "print(media,var)\n", "ds_hist_norm= (ds_hist-media)/var\n", "print(np.mean(ds_hist_norm),np.std(ds_hist_norm))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15,6))\n", "plt.subplot(3,1,1)\n", "plt.hist(ds_hist,bins=1000)\n", "plt.subplot(3,1,2)\n", "plt.hist(ds_hist_per,bins=1000)\n", "plt.subplot(3,1,3)\n", "plt.hist(ds_hist_norm,bins=1000)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Un ejemplo de la normalización\n", "fp = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\"\n", "allfiles = os.listdir(fp)\n", "ds_suj = []\n", "for file in allfiles:\n", " path = os.path.join(fp,file)\n", " if not os.path.isdir(path):\n", " if \"sujeto\" in file:\n", " ds_suj.append(os.path.join(fp,file))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "x = nib.load(ds_suj[1])\n", "x = x.get_fdata()\n", "x_nyul = nyul_apply_standard_scale(x, standard_path)\n", "x_norm = np.clip(x_nyul,p1,p2)\n", "x_norm = (x_norm-media)/var\n", "\n", "plt.figure(figsize=(15, 10))\n", "plt.subplot(331)\n", "plt.hist(x.flatten(), bins=1000)\n", "plt.subplot(332)\n", "plt.hist(x_nyul.flatten(), bins=1000)\n", "plt.subplot(333)\n", "plt.hist(x_norm.flatten(), bins=1000)\n", "plt.subplot(334)\n", "plt.imshow(x[63:319,63:319,10], cmap='gray')\n", "plt.subplot(335)\n", "plt.imshow(x_nyul[63:319,63:319,10], cmap='gray')\n", "plt.subplot(336)\n", "plt.imshow(x_norm[63:319,63:319,10], cmap='gray')\n", "plt.show()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Creo las slices aplicando Nyul + z-score normalization. Guardo en formato .npy" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fp0 = [r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\mascaras\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\validation_data\\mascaras\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\test_data\\mascaras\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\\sujetos\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\validation_data\\sujetos\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\test_data\\sujetos\"]" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "\n", "fp0 = [r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\validation_data\",\n", " r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\test_data\"]" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "for fp in fp0:\n", " if \"train\" in fp: name = \"train\"\n", " elif \"test\" in fp: name = \"test\"\n", " elif \"validation\" in fp: name = \"val\"\n", " cont = 0\n", " cont2 = 0\n", "\n", " for file in sorted(os.listdir(fp)):\n", " path = os.path.join(fp,file)\n", " if not os.path.isdir(path):\n", " x = nib.load(path)\n", " y = x.get_fdata()\n", " if \"sujeto\" in file:\n", " y = nyul_apply_standard_scale(y, standard_path)\n", " for slices in range(np.size(y,2)):\n", " cont+=1\n", " img = y[63:319,63:319,slices]\n", " #img = np.clip(y[63:319,63:319,slices],p1,p2)\n", " img = (img-media)/var \n", " np.save(fp+\"\\img_sujeto_\"+name+\"_\"+str(cont).zfill(4),img)\n", " else:\n", " for slices in range(np.size(y,2)):\n", " cont2+=1\n", " img = y[63:319,63:319,slices]\n", " np.save(fp+\"\\img_segmentacion_\"+name+\"_\"+str(cont2).zfill(4),img) " ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "DATA AUGMENTATION" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "#p1, p2 = -107.75208459640474, 128.45794968358558\n", "#media, var = 3.4506247419236113, 42.43344987315689" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "fp = r\"C:\\Users\\Pier\\Desktop\\PFI_main\\DS_VOLUMEN\\main\\train_data\"\n", "cont = len(os.listdir(fp+\"\\sujetos\"))\n", "\n", "for file in sorted(os.listdir(fp)):\n", " path = os.path.join(fp,file)\n", " if not os.path.isdir(path):\n", " if \"sujeto_\" in file:\n", " x = nib.load(path)\n", " y = x.get_fdata()\n", " y = nyul_apply_standard_scale(y, standard_path)\n", " for slice in range(np.size(y,2)):\n", " if np.random.randint(0,100) > 50:\n", " a = nib.load(os.path.join(fp,\"segmentacion_\"+file[-7:]))\n", " a = a.get_fdata()\n", " cont += 1\n", " img_deformed,seg_deformed = elasticdeform.deform_random_grid([y[:,:,slice],a[:,:,slice]], sigma=5, points=10)\n", " img = img_deformed[63:319,63:319]\n", " #img = np.clip(img_deformed[63:319,63:319],p1,p2)\n", " img = (img-media)/var\n", " seg = seg_deformed[63:319,63:319]\n", " np.save(fp+\"\\img_sujeto_train_\"+str(cont).zfill(4),img)\n", " np.save(fp+\"\\img_segmentacion_train_\"+str(cont).zfill(4),seg) " ] } ], "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": "3.8.0" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "a8e68cbbe928a735cbef36e0c504d1e4907a06cf8776305a5ea24ea01ddf5907" } } }, "nbformat": 4, "nbformat_minor": 2 }