meanStd.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd  \n",
    "import importlib\n",
    "import os\n",
    "import numpy as np\n",
    "from skimage import measure\n",
    "from ipywidgets import interact\n",
    "from ipywidgets import interact_manual\n",
    "from IPython.display import display\n",
    "from ipywidgets import widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'ipynb.fs.full.dicomHandler' (/mnt/6884ACCB84AC9CD6/OneDrive - FEI/Aulas/Graduacao/8 - Semestre/CC8421 - TRABALHO FINAL DE CURSO II/image-segmentation/dicomHandler.ipynb)>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import ipynb.fs.full.wspFFA as wspFirefly\n",
    "import ipynb.fs.full.wspCS as wspCuckooSearch\n",
    "import ipynb.fs.full.wspKH as wspKrillHerd\n",
    "import ipynb.fs.full.wspEHO as wspElephantHerding\n",
    "import ipynb.fs.full.wspABC as wspArtificialBeeColony\n",
    "\n",
    "import ipynb.fs.full.plotGraph as plotGraph\n",
    "import ipynb.fs.full.wspMultithreshold as wspMultithreshold\n",
    "import ipynb.fs.full.dicomHandler as dicomHandler\n",
    "\n",
    "importlib.reload(wspFirefly)\n",
    "importlib.reload(wspCuckooSearch)\n",
    "importlib.reload(wspKrillHerd)\n",
    "importlib.reload(wspElephantHerding)\n",
    "importlib.reload(wspArtificialBeeColony)\n",
    "\n",
    "importlib.reload(plotGraph)\n",
    "importlib.reload(wspMultithreshold)\n",
    "importlib.reload(dicomHandler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "folder_dir = \"../Database/2EFVJVCN/\"\n",
    "file = \"I1680000\"\n",
    "bio_algorithms = 'FFA'\n",
    "dimension = 2\n",
    "q = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "image = folder_dir + file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dicom_image, pixel_array = dicomHandler.read_dicom_image(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dataset.file_meta -------------------------------\n",
       "(0002, 0000) File Meta Information Group Length  UL: 168\n",
       "(0002, 0001) File Meta Information Version       OB: b'\\x00\\x01'\n",
       "(0002, 0002) Media Storage SOP Class UID         UI: CT Image Storage\n",
       "(0002, 0003) Media Storage SOP Instance UID      UI: 1.3.12.2.1107.5.1.4.105159.30000021013010280633300022620\n",
       "(0002, 0010) Transfer Syntax UID                 UI: Explicit VR Little Endian\n",
       "(0002, 0012) Implementation Class UID            UI: 1.2.840.113704.7.0.2\n",
       "-------------------------------------------------\n",
       "(0008, 0005) Specific Character Set              CS: 'ISO_IR 100'\n",
       "(0008, 0008) Image Type                          CS: ['ORIGINAL', 'PRIMARY', 'AXIAL', 'CT_SOM5 SPI']\n",
       "(0008, 0016) SOP Class UID                       UI: CT Image Storage\n",
       "(0008, 0018) SOP Instance UID                    UI: 1.3.12.2.1107.5.1.4.105159.30000021013010280633300022620\n",
       "(0008, 0020) Study Date                          DA: '20210130'\n",
       "(0008, 0021) Series Date                         DA: '20210130'\n",
       "(0008, 0022) Acquisition Date                    DA: '20210130'\n",
       "(0008, 0023) Content Date                        DA: '20210130'\n",
       "(0008, 002a) Acquisition DateTime                DT: '20210130105641.101000'\n",
       "(0008, 0030) Study Time                          TM: '105358'\n",
       "(0008, 0031) Series Time                         TM: '105707'\n",
       "(0008, 0032) Acquisition Time                    TM: '105641.101000'\n",
       "(0008, 0033) Content Time                        TM: '105641.101000'\n",
       "(0008, 0050) Accession Number                    SH: '23303965'\n",
       "(0008, 0060) Modality                            CS: 'CT'\n",
       "(0008, 0061) Modalities in Study                 CS: ['CT', 'SR']\n",
       "(0008, 0070) Manufacturer                        LO: 'SIEMENS'\n",
       "(0008, 0080) Institution Name                    LO: 'HCOR DIAGNOSTICO - CID. JARDIM'\n",
       "(0008, 0081) Institution Address                 ST: 'Street\\r\\nCity\\r\\nDistrict\\r\\nBR'\n",
       "(0008, 0090) Referring Physician's Name          PN: 'FERNANDO MELHEM ELIAS'\n",
       "(0008, 1010) Station Name                        SH: 'CTAWP105159'\n",
       "(0008, 1030) Study Description                   LO: 'TC Seios da Face'\n",
       "(0008, 1032)  Procedure Code Sequence  1 item(s) ---- \n",
       "\n",
       "   ---------\n",
       "(0008, 103e) Series Description                  LO: 'VOLUMETRICO'\n",
       "(0008, 1070) Operators' Name                     PN: 'Helio'\n",
       "(0008, 1090) Manufacturer's Model Name           LO: 'SOMATOM Drive'\n",
       "(0008, 1120)  Referenced Patient Sequence  1 item(s) ---- \n",
       "   (0008, 1150) Referenced SOP Class UID            UI: Detached Patient Management SOP Class\n",
       "   (0008, 1155) Referenced SOP Instance UID         UI: ''\n",
       "   ---------\n",
       "(0008, 1140)  Referenced Image Sequence  1 item(s) ---- \n",
       "   (0008, 1150) Referenced SOP Class UID            UI: CT Image Storage\n",
       "   (0008, 1155) Referenced SOP Instance UID         UI: 1.3.12.2.1107.5.1.4.105159.30000021013009501555100002159\n",
       "   ---------\n",
       "(0008, 2112)  Source Image Sequence  1 item(s) ---- \n",
       "   (0008, 1150) Referenced SOP Class UID            UI: 1.3.12.2.1107.5.9.1\n",
       "   (0008, 1155) Referenced SOP Instance UID         UI: 1.3.12.2.1107.5.1.4.105159.30000021013010213304100000066\n",
       "   ---------\n",
       "(0008, 3010) Irradiation Event UID               UI: 1.3.12.2.1107.5.1.4.105159.30000021013010213304100000066\n",
       "(0009, 0010) Private Creator                     LO: 'SIEMENS CT VA1 DUMMY'\n",
       "(0010, 0010) Patient's Name                      PN: 'SANTOS^MARIA FREITAS'\n",
       "(0010, 0020) Patient ID                          LO: '8398976'\n",
       "(0010, 0021) Issuer of Patient ID                LO: 'CSH'\n",
       "(0010, 0030) Patient's Birth Date                DA: '20011205'\n",
       "(0010, 0040) Patient's Sex                       CS: 'F'\n",
       "(0010, 1010) Patient's Age                       AS: '019Y'\n",
       "(0010, 21c0) Pregnancy Status                    US: 0\n",
       "(0018, 0015) Body Part Examined                  CS: 'HEAD'\n",
       "(0018, 0050) Slice Thickness                     DS: '0.6'\n",
       "(0018, 0060) KVP                                 DS: '100.0'\n",
       "(0018, 0090) Data Collection Diameter            DS: '500.0'\n",
       "(0018, 1000) Device Serial Number                LO: '105159'\n",
       "(0018, 1020) Software Versions                   LO: 'syngo CT VB10A'\n",
       "(0018, 1030) Protocol Name                       LO: 'NEURONAVEGACAO_Si'\n",
       "(0018, 1100) Reconstruction Diameter             DS: '210.0'\n",
       "(0018, 1110) Distance Source to Detector         DS: '1085.6'\n",
       "(0018, 1111) Distance Source to Patient          DS: '595.0'\n",
       "(0018, 1120) Gantry/Detector Tilt                DS: '0.0'\n",
       "(0018, 1130) Table Height                        DS: '154.5'\n",
       "(0018, 1140) Rotation Direction                  CS: 'CW'\n",
       "(0018, 1150) Exposure Time                       IS: '1000'\n",
       "(0018, 1151) X-Ray Tube Current                  IS: '50'\n",
       "(0018, 1152) Exposure                            IS: '62'\n",
       "(0018, 1160) Filter Type                         SH: 'FLAT'\n",
       "(0018, 1170) Generator Power                     IS: '9'\n",
       "(0018, 1190) Focal Spot(s)                       DS: '1.2'\n",
       "(0018, 1200) Date of Last Calibration            DA: '20210130'\n",
       "(0018, 1201) Time of Last Calibration            TM: ''\n",
       "(0018, 1210) Convolution Kernel                  SH: ['Hr32s', '3']\n",
       "(0018, 5100) Patient Position                    CS: 'HFS'\n",
       "(0018, 9306) Single Collimation Width            FD: 0.6\n",
       "(0018, 9307) Total Collimation Width             FD: 38.4\n",
       "(0018, 9309) Table Speed                         FD: 30.7\n",
       "(0018, 9310) Table Feed per Rotation             FD: 30.7\n",
       "(0018, 9311) Spiral Pitch Factor                 FD: 0.8\n",
       "(0018, 9313) Data Collection Center (Patient)    FD: [0.0, -154.5, 119.4]\n",
       "(0018, 9318) Reconstruction Target Center (Patie FD: [-1.0, -151.5, 119.4]\n",
       "(0018, 9323) Exposure Modulation Type            CS: 'Z_EC'\n",
       "(0018, 9324) Estimated Dose Saving               FD: 66.5799\n",
       "(0018, 9345) CTDIvol                             FD: 9.88279\n",
       "(0018, 9346)  CTDI Phantom Type Code Sequence  1 item(s) ---- \n",
       "   (0008, 0100) Code Value                          SH: '113690'\n",
       "   (0008, 0102) Coding Scheme Designator            SH: 'DCM'\n",
       "   (0008, 0104) Code Meaning                        LO: 'IEC Head Dosimetry Phantom'\n",
       "   ---------\n",
       "(0019, 0010) Private Creator                     LO: 'SIEMENS CT VA0  COAD'\n",
       "(0020, 000d) Study Instance UID                  UI: 1.2.840.55555.862678190.20210130101637322.20788\n",
       "(0020, 000e) Series Instance UID                 UI: 1.3.12.2.1107.5.1.4.105159.30000021013010280633300022452\n",
       "(0020, 0010) Study ID                            SH: 'TCSF'\n",
       "(0020, 0011) Series Number                       IS: '3'\n",
       "(0020, 0012) Acquisition Number                  IS: '3'\n",
       "(0020, 0013) Instance Number                     IS: '168'\n",
       "(0020, 0032) Image Position (Patient)            DS: [-105.794921875, -256.294921875, 119.4]\n",
       "(0020, 0037) Image Orientation (Patient)         DS: [1, 0, 0, 0, 1, 0]\n",
       "(0020, 0052) Frame of Reference UID              UI: 1.3.12.2.1107.5.1.4.105159.30000021013010213304100000062\n",
       "(0020, 1040) Position Reference Indicator        LO: ''\n",
       "(0020, 1041) Slice Location                      DS: '119.4'\n",
       "(0020, 1208) Number of Study Related Instances   IS: '721'\n",
       "(0020, 4000) Image Comments                      LT: ''\n",
       "(0021, 0010) Private Creator                     LO: 'SIEMENS MED'\n",
       "(0028, 0002) Samples per Pixel                   US: 1\n",
       "(0028, 0004) Photometric Interpretation          CS: 'MONOCHROME2'\n",
       "(0028, 0010) Rows                                US: 512\n",
       "(0028, 0011) Columns                             US: 512\n",
       "(0028, 0030) Pixel Spacing                       DS: [0.41015625, 0.41015625]\n",
       "(0028, 0100) Bits Allocated                      US: 16\n",
       "(0028, 0101) Bits Stored                         US: 12\n",
       "(0028, 0102) High Bit                            US: 11\n",
       "(0028, 0103) Pixel Representation                US: 0\n",
       "(0028, 0106) Smallest Image Pixel Value          US: 0\n",
       "(0028, 0107) Largest Image Pixel Value           US: 2946\n",
       "(0028, 1050) Window Center                       DS: [30, -700]\n",
       "(0028, 1051) Window Width                        DS: [420, 1600]\n",
       "(0028, 1052) Rescale Intercept                   DS: '-1024.0'\n",
       "(0028, 1053) Rescale Slope                       DS: '1.0'\n",
       "(0028, 1054) Rescale Type                        LO: 'HU'\n",
       "(0028, 1055) Window Center & Width Explanation   LO: ['WINDOW1', 'WINDOW2']\n",
       "(0029, 0010) Private Creator                     LO: 'SIEMENS CSA HEADER'\n",
       "(0029, 0011) Private Creator                     LO: 'SIEMENS MEDCOM HEADER'\n",
       "(0032, 1060) Requested Procedure Description     LO: 'TC Seios da Face'\n",
       "(0032, 1064)  Requested Procedure Code Sequence  1 item(s) ---- \n",
       "\n",
       "   ---------\n",
       "(0040, 0275)  Request Attributes Sequence  1 item(s) ---- \n",
       "   (0040, 0008)  Scheduled Protocol Code Sequence  1 item(s) ---- \n",
       "\n",
       "      ---------\n",
       "   (0040, 0009) Scheduled Procedure Step ID         SH: '9274005706170'\n",
       "   (0040, 1001) Requested Procedure ID              SH: 'TCSF'\n",
       "   ---------\n",
       "(0040, 1008) Confidentiality Code                LO: 'N'\n",
       "(0088, 0200)  Icon Image Sequence  1 item(s) ---- \n",
       "   (0028, 0002) Samples per Pixel                   US: 1\n",
       "   (0028, 0004) Photometric Interpretation          CS: 'MONOCHROME2'\n",
       "   (0028, 0010) Rows                                US: 64\n",
       "   (0028, 0011) Columns                             US: 64\n",
       "   (0028, 0034) Pixel Aspect Ratio                  IS: [1, 1]\n",
       "   (0028, 0100) Bits Allocated                      US: 8\n",
       "   (0028, 0101) Bits Stored                         US: 8\n",
       "   (0028, 0102) High Bit                            US: 7\n",
       "   (0028, 0103) Pixel Representation                US: 0\n",
       "   (7fe0, 0010) Pixel Data                          OB: Array of 4096 elements\n",
       "   ---------\n",
       "(07a1, 0010) Private Creator                     LO: 'ELSCINT1'\n",
       "(07a1, 1002) [number of images in series]        UL: 358\n",
       "(07a1, 102a) [Tamar Study Status]                CS: 'READ'\n",
       "(07a1, 1040) [Tamar Study Body Part]             CS: 'CRANIO'\n",
       "(07a1, 1042) Private tag data                    SH: 'NOT ASSIGNED'\n",
       "(07a1, 1043) [Unknown]                           IS: '3'\n",
       "(07a1, 1050) [Tamar Site Id]                     US: 0\n",
       "(07a1, 1058) Private tag data                    CS: 'A'\n",
       "(07a1, 105d) Private tag data                    DT: '20210130105739.000000'\n",
       "(07a1, 105f) Private tag data                    CS: 'N'\n",
       "(07a1, 1085) [Tamar Translate Flags]             UL: 3\n",
       "(07a1, 10a7) Private tag data                    LO: '42135'\n",
       "(07a1, 10d0) Private tag data                    LO: '34130696667137'\n",
       "(07a3, 0010) Private Creator                     LO: 'ELSCINT1'\n",
       "(07a3, 1001) [Tamar Exe Software Version]        LO: '12.2.1.2'\n",
       "(07a3, 1003) [Tamar Study Has Sticky Note]       CS: 'N'\n",
       "(07a3, 1014) Private tag data                    ST: 'STCSF'\n",
       "(07a3, 1017) Private tag data                    SH: 'CM'\n",
       "(07a3, 101b) Private tag data                    ST: 'CRM 136616'\n",
       "(07a3, 101c) Private tag data                    ST: 'Freddi'\n",
       "(07a3, 101d) Private tag data                    ST: 'Dr. Tomas de A. L.'\n",
       "(07a3, 101e) Private tag data                    ST: 'CRM 136616'\n",
       "(07a3, 1022) Private tag data                    ST: 'E'\n",
       "(07a3, 1024) Private tag data                    ST: 'N'\n",
       "(07a3, 1055) [Unknown]                           SH: 'N'\n",
       "(07a3, 105c) Private tag data                    ST: '0'\n",
       "(07a3, 108c) Private tag data                    CS: 'N'\n",
       "(07a3, 108f) Private tag data                    CS: 'N'\n",
       "(07a3, 109c) [Unknown]                           CS: 'N'\n",
       "(07a3, 10b9) Private tag data                    CS: 'N'\n",
       "(07a3, 10bb) Private tag data                    CS: 'N'\n",
       "(07a3, 10c0)  Private tag data  1 item(s) ---- \n",
       "   (07a3, 0010) Private Creator                     LO: 'ELSCINT1'\n",
       "   (07a3, 1039) Private tag data                    UL: 61\n",
       "   (07a3, 10c1) Private tag data                    LO: 'pacs_GN'\n",
       "   (07a3, 10c2) Private tag data                    CS: 'FAST_NET'\n",
       "   (07a3, 10c3) Private tag data                    CS: 'SECURED_CON'\n",
       "   (07a3, 10c4) Private tag data                    LO: '191.1.12.100'\n",
       "   (07a3, 10c5) Private tag data                    LO: '22104'\n",
       "   (07a3, 10c8) Private tag data                    AE: 'pacsFIR'\n",
       "   (07a3, 10c9) Private tag data                    CS: 'N'\n",
       "   (07a3, 10cc) Private tag data                    LO: '1.0.0.0'\n",
       "   ---------\n",
       "(07a3, 10ca)  Private tag data  1 item(s) ---- \n",
       "   (07a3, 0010) Private Creator                     LO: 'ELSCINT1'\n",
       "   (07a3, 1039) Private tag data                    UL: 61\n",
       "   (07a3, 10c1) Private tag data                    LO: 'pacs_GN'\n",
       "   (07a3, 10c2) Private tag data                    CS: 'FAST_NET'\n",
       "   (07a3, 10c3) Private tag data                    CS: 'SECURED_CON'\n",
       "   (07a3, 10c4) Private tag data                    LO: '191.1.12.100'\n",
       "   (07a3, 10c5) Private tag data                    LO: '22104'\n",
       "   (07a3, 10c8) Private tag data                    AE: 'pacsFIR'\n",
       "   (07a3, 10c9) Private tag data                    CS: 'N'\n",
       "   (07a3, 10cc) Private tag data                    LO: '1.0.0.0'\n",
       "   ---------\n",
       "(07a3, 10cb)  Private tag data  1 item(s) ---- \n",
       "   (07a3, 0010) Private Creator                     LO: 'ELSCINT1'\n",
       "   (07a3, 1039) Private tag data                    UL: 61\n",
       "   (07a3, 10c1) Private tag data                    LO: 'pacs_GN'\n",
       "   (07a3, 10c2) Private tag data                    CS: 'FAST_NET'\n",
       "   (07a3, 10c3) Private tag data                    CS: 'SECURED_CON'\n",
       "   (07a3, 10c4) Private tag data                    LO: '191.1.12.100'\n",
       "   (07a3, 10c5) Private tag data                    LO: '22104'\n",
       "   (07a3, 10c8) Private tag data                    AE: 'pacsFIR'\n",
       "   (07a3, 10c9) Private tag data                    CS: 'N'\n",
       "   (07a3, 10cc) Private tag data                    LO: '1.0.0.0'\n",
       "   ---------\n",
       "(07a5, 0010) Private Creator                     LO: 'ELSCINT1'\n",
       "(07a5, 1010) Private tag data                    UL: 1\n",
       "(07a5, 1054) Private tag data                    DT: '20210201143739.000000'\n",
       "(07a5, 1056) Private tag data                    CS: 'N'\n",
       "(07a5, 1059) Private tag data                    IS: '0'\n",
       "(07a5, 1069) Private tag data                    AE: 'CTAWP105159_U'\n",
       "(07a5, 1072) Private tag data                    DT: '20210130105739.000000'\n",
       "(07a5, 10c8) Private tag data                    CS: 'Y'\n",
       "(07a5, 10dc) Private tag data                    UL: 500\n",
       "(07a5, 10dd) Private tag data                    FL: 2.0\n",
       "(07a5, 10de) Private tag data                    LO: 'N/A'\n",
       "(07a5, 10e8) Private tag data                    IS: '0'\n",
       "(7fe0, 0010) Pixel Data                          OW: Array of 524288 elements"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dicom_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'-1024.0'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dicom_image.RescaleIntercept"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dicom_image.RescaleSlope"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 2946\n",
      "-1024.0 1922.0\n"
     ]
    }
   ],
   "source": [
    "dicom_image, pixel_array = dicomHandler.read_dicom_image(image)\n",
    "\n",
    "transformed_pixel_array = dicomHandler.image_transformation(pixel_array)\n",
    "\n",
    "original_image = pixel_array.copy()\n",
    "\n",
    "print(pixel_array.min(), pixel_array.max())\n",
    "    \n",
    "hu_image = dicomHandler.transform_to_hu(dicom_image, transformed_pixel_array)\n",
    "\n",
    "print(hu_image.min(), hu_image.max())\n",
    "\n",
    "hist, bin_edges, best_thresholds, img_thres = wspMultithreshold.wspMultithreshold(hu_image, bio_algorithms, dimension, q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-1024.0 1923.0\n",
      "-1024.0 1923.0\n",
      "0 2947\n",
      "0 2947\n"
     ]
    }
   ],
   "source": [
    "high_intensity = wspMultithreshold.get_high_intensity_pixels(img_thres)\n",
    "\n",
    "print(high_intensity.min(), high_intensity.max())\n",
    "\n",
    "pixel_array = dicomHandler.transform_to_pixel_array(dicom_image, high_intensity)\n",
    "\n",
    "print(pixel_array.min(), pixel_array.max())\n",
    "\n",
    "hard_tissue = wspMultithreshold.get_largests_regions(pixel_array, original_image)\n",
    "\n",
    "print(hard_tissue.min(), hard_tissue.max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dicomHandler.show_dicom_image(pixel_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dicomHandler.show_dicom_image(hu_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 2946\n"
     ]
    }
   ],
   "source": [
    "min_val, max_val = original_image.min(), original_image.max()\n",
    "print(min_val, max_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "org = original_image.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = np.where(pixel_array==pixel_array.max(), False, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dicomHandler.show_dicom_image(mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "org[mask] = org.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dicomHandler.show_dicom_image(org)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    }
   ],
   "source": [
    "from skimage import data, util, measure\n",
    "\n",
    "def region_stdev(region, intensities):\n",
    "    return np.std(intensities[region])\n",
    "\n",
    "label_image = measure.label(pixel_array)\n",
    "props = measure.regionprops_table(label_image, original_image, properties=['area', 'intensity_mean'], extra_properties=[region_stdev])\n",
    "\n",
    "table = pd.DataFrame(props)\n",
    "X_train = table.values.tolist()\n",
    "print(table['area'].idxmax())\n",
    "\n",
    "#sorted_table = table.sort_values(by='area', ascending=False)\n",
    "#sorted_table.reset_index(drop=True, inplace=True)\n",
    "#sorted_table.rename(columns={'area': 'Area', 'intensity_mean': 'Mean', 'region_stdev': 'Std'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "\n",
    "scaler = preprocessing.StandardScaler().fit(X_train)\n",
    "\n",
    "X_scaled = scaler.transform(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "kmeans = KMeans(n_clusters=2, random_state=2).fit(X_scaled)\n",
    "\n",
    "included_labels = kmeans.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0], dtype=int32)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "included_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_largest_region(pixel_array):\n",
    "    max_value = pixel_array.max()\n",
    "    min_value = pixel_array.min()\n",
    "\n",
    "    labels_mask = measure.label(pixel_array)\n",
    "\n",
    "    regions = measure.regionprops(labels_mask)\n",
    "    #regions.sort(key=lambda x: x.area, reverse=True)\n",
    "    \n",
    "    if len(regions) > 1:\n",
    "        for index in range(len(regions)):\n",
    "            if not included_labels[index]:\n",
    "                labels_mask[regions[index].coords[:,0], regions[index].coords[:,1]] = min_value\n",
    "\n",
    "    labels_mask[labels_mask != min_value] = max_value\n",
    "    mask = labels_mask\n",
    "\n",
    "    return mask.astype(np.int16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "teste = get_largest_region(pixel_array)\n",
    "dicomHandler.show_dicom_image(teste)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.4 ('tcc_env')",
   "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": "3.10.4"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "50c3a715107fe4dcdc7dcc1225e41dc08fefd31cb688eb0c1f730ec66093fb86"
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