├── .gitignore ├── lungs_finder ├── __init__.py ├── lbp_finder.py ├── haar_finder.py ├── hog_finder.py ├── find_tools.py ├── right_lung_lbp.xml ├── left_lung_lbp.xml ├── left_lung_hog.np ├── right_lung_hog.np ├── right_lung_haar.xml └── left_lung_haar.xml ├── setup.py ├── README.md ├── lungs_viewer.py └── LICENSE /.gitignore: -------------------------------------------------------------------------------- 1 | .idea/* -------------------------------------------------------------------------------- /lungs_finder/__init__.py: -------------------------------------------------------------------------------- 1 | from lungs_finder.haar_finder import * 2 | from lungs_finder.hog_finder import * 3 | from lungs_finder.lbp_finder import * 4 | from lungs_finder.find_tools import get_lungs 5 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import setup, find_packages 2 | 3 | setup( 4 | name="lungs_finder", 5 | version="1.0.0", 6 | description="Library that helps you to find lungs on chest X-ray (CXR) images for further processing", 7 | author="Maksym Kholiavchenko", 8 | author_email="dirtmaxim@gmail.com", 9 | url="https://github.com/dirtmaxim/lungs-finder", 10 | download_url="https://github.com/dirtmaxim/lungs-finder/archive/1.0.0.tar.gz", 11 | license="Apache-2.0", 12 | packages=find_packages(), 13 | package_data={"lungs_finder": ["*.xml", "*.np"]} 14 | ) 15 | -------------------------------------------------------------------------------- /lungs_finder/lbp_finder.py: -------------------------------------------------------------------------------- 1 | import os 2 | import cv2 3 | from . import find_tools as ft 4 | 5 | 6 | def find_right_lung_lbp(image): 7 | right_lung = cv2.CascadeClassifier(os.path.dirname(__file__) + os.sep + "right_lung_lbp.xml") 8 | found = right_lung.detectMultiScale(image, 1.8, 5) 9 | right_lung_rectangle = ft.find_max_rectangle(found) 10 | 11 | return right_lung_rectangle 12 | 13 | 14 | def find_left_lung_lbp(image): 15 | left_lung = cv2.CascadeClassifier(os.path.dirname(__file__) + os.sep + "left_lung_lbp.xml") 16 | found = left_lung.detectMultiScale(image, 1.8, 5) 17 | left_lung_rectangle = ft.find_max_rectangle(found) 18 | 19 | return left_lung_rectangle 20 | -------------------------------------------------------------------------------- /lungs_finder/haar_finder.py: -------------------------------------------------------------------------------- 1 | import os 2 | import cv2 3 | from . import find_tools as ft 4 | 5 | 6 | def find_right_lung_haar(image): 7 | right_lung = cv2.CascadeClassifier(os.path.dirname(__file__) + os.sep + "right_lung_haar.xml") 8 | found = right_lung.detectMultiScale(image, 1.8, 5) 9 | right_lung_rectangle = ft.find_max_rectangle(found) 10 | 11 | return right_lung_rectangle 12 | 13 | 14 | def find_left_lung_haar(image): 15 | left_lung = cv2.CascadeClassifier(os.path.dirname(__file__) + os.sep + "left_lung_haar.xml") 16 | found = left_lung.detectMultiScale(image, 1.8, 5) 17 | left_lung_rectangle = ft.find_max_rectangle(found) 18 | 19 | return left_lung_rectangle 20 | -------------------------------------------------------------------------------- /lungs_finder/hog_finder.py: -------------------------------------------------------------------------------- 1 | import os 2 | import numpy as np 3 | import cv2 4 | from . import find_tools as ft 5 | 6 | # noinspection PyArgumentList 7 | hog = cv2.HOGDescriptor((32, 64), (16, 16), (8, 8), (8, 8), 9, 1, 4, 0, 0.2, 0, 64) 8 | 9 | 10 | def find_right_lung_hog(image): 11 | hog.setSVMDetector( 12 | np.loadtxt(os.path.dirname(__file__) + os.sep + "right_lung_hog.np", dtype=np.float32)) 13 | found, w = hog.detectMultiScale(image) 14 | right_lung_rectangle = ft.find_max_rectangle(found) 15 | 16 | return right_lung_rectangle 17 | 18 | 19 | def find_left_lung_hog(image): 20 | hog.setSVMDetector(np.loadtxt(os.path.dirname(__file__) + os.sep + "left_lung_hog.np", dtype=np.float32)) 21 | found, w = hog.detectMultiScale(image) 22 | left_lung_rectangle = ft.find_max_rectangle(found) 23 | 24 | return left_lung_rectangle 25 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # lungs-finder 2 | 3 | ##### Library for lungs detection on CXR images 4 | 5 | ![](https://user-images.githubusercontent.com/11778655/27996147-765dfba8-64e4-11e7-81ca-9ea25b5d072d.png) 6 | 7 | ``` 8 | Requirements: 9 | - Python 3; 10 | - OpenCV3. 11 | ``` 12 | 13 | ``` 14 | Installation: 15 | - pip install lungs-finder 16 | ``` 17 | 18 | ``` 19 | You can test your dataset using lungs_viewer.py. 20 | It is a program that is displayed on the screenshot above. 21 | Usage: lungs_viewer.py /your/dataset True 22 | The last parameter defines whether labels will be displayed or not. 23 | ``` 24 | 25 | ``` 26 | You can get lungs using HOG, Haar or LBP. 27 | Example: 28 | 29 | import lungs_finder as lf 30 | 31 | image = cv2.imread("/your/image/cxr.png", 0) 32 | 33 | # Get both lungs image. It uses HOG as main method, 34 | # but if HOG found nothing it uses HAAR or LBP. 35 | found_lungs = lf.get_lungs(image) 36 | 37 | if found_lungs is not None: 38 | cv2.imshow("Found lungs", found_lungs) 39 | code = cv2.waitKey(0) 40 | 41 | # Or you can get left or right lung independently using HOG, Haar or LBP. 42 | right_lung_hog_rectangle = lf.find_right_lung_hog(scaled_image) 43 | left_lung_hog_rectangle = lf.find_left_lung_hog(scaled_image) 44 | right_lung_lbp_rectangle = lf.find_right_lung_lbp(scaled_image) 45 | left_lung_lbp_rectangle = lf.find_left_lung_lbp(scaled_image) 46 | right_lung_haar_rectangle = lf.find_right_lung_haar(scaled_image) 47 | left_lung_haar_rectangle = lf.find_left_lung_haar(scaled_image) 48 | 49 | if right_lung_hog_rectangle is not None: 50 | x, y, width, height = right_lung_hog_rectangle 51 | right_image = image[y:y + height, x:x + width] 52 | cv2.imshow("Right lung", right_image) 53 | code = cv2.waitKey(0) 54 | ``` 55 | -------------------------------------------------------------------------------- /lungs_finder/find_tools.py: -------------------------------------------------------------------------------- 1 | from . import haar_finder 2 | from . import hog_finder 3 | from . import lbp_finder 4 | 5 | 6 | def find_max_rectangle(rectangles): 7 | max_rectangle = None 8 | max_area = 0 9 | 10 | for rectangle in rectangles: 11 | x, y, width, height = rectangle 12 | area = width * height 13 | 14 | if area > max_area: 15 | max_area = area 16 | max_rectangle = rectangle 17 | 18 | return max_rectangle 19 | 20 | 21 | def get_lungs(image, padding=15): 22 | right_lung = hog_finder.find_right_lung_hog(image) 23 | left_lung = hog_finder.find_left_lung_hog(image) 24 | 25 | if right_lung is not None and left_lung is not None: 26 | x_right, y_right, width_right, height_right = right_lung 27 | x_left, y_left, width_left, height_left = left_lung 28 | 29 | if abs(x_right - x_left) < min(width_right, width_left): 30 | right_lung = lbp_finder.find_right_lung_lbp(image) 31 | left_lung = lbp_finder.find_left_lung_lbp(image) 32 | 33 | if right_lung is None: 34 | right_lung = haar_finder.find_right_lung_haar(image) 35 | 36 | if left_lung is None: 37 | left_lung = haar_finder.find_left_lung_haar(image) 38 | 39 | if right_lung is None: 40 | right_lung = lbp_finder.find_right_lung_lbp(image) 41 | 42 | if left_lung is None: 43 | left_lung = lbp_finder.find_left_lung_lbp(image) 44 | 45 | if right_lung is None and left_lung is None: 46 | return None 47 | elif right_lung is None: 48 | x, y, width, height = left_lung 49 | spine = width / 5 50 | right_lung = int(x - width - spine), y, width, height 51 | elif left_lung is None: 52 | x, y, width, height = right_lung 53 | spine = width / 5 54 | left_lung = int(x + width + spine), y, width, height 55 | 56 | x_right, y_right, _, height_right = right_lung 57 | x_left, y_left, width_left, height_left = left_lung 58 | x_right -= padding 59 | y_right -= padding 60 | height_right += padding * 2 61 | y_left -= padding 62 | width_left += padding 63 | height_left += padding * 2 64 | 65 | if x_right < 0: 66 | x_right = 0 67 | 68 | if y_right < 0: 69 | y_right = 0 70 | 71 | if x_left < 0: 72 | x_left = 0 73 | 74 | if y_left < 0: 75 | y_left = 0 76 | 77 | if y_right + height_right > image.shape[0]: 78 | height_right = image.shape[0] - y_right 79 | 80 | if x_left + width_left > image.shape[1]: 81 | width_left = image.shape[1] - x_left 82 | 83 | if y_left + height_left > image.shape[0]: 84 | height_left = image.shape[0] - y_left 85 | 86 | top_y = min(y_right, y_left) 87 | bottom_y = max(y_right + height_right, y_left + height_left) 88 | 89 | return image[top_y:bottom_y, x_right:x_left + width_left] 90 | -------------------------------------------------------------------------------- /lungs_viewer.py: -------------------------------------------------------------------------------- 1 | import os 2 | import sys 3 | import numpy as np 4 | import cv2 5 | import lungs_finder as lf 6 | 7 | try: 8 | __import__("imp").find_module("dicompylercore") 9 | from dicompylercore import dicomparser 10 | 11 | dicom_support = True 12 | except ImportError: 13 | dicom_support = False 14 | print("\"dicompylercore\" library was not found. \"lungs-finder\" works without dicom support.") 15 | 16 | 17 | def parse_argv(argv): 18 | if len(argv) != 3: 19 | print("Usage: lungs_viewer.py \"path_to_folder\" \"use_labels\".") 20 | exit(1) 21 | 22 | path_to_folder = argv[1] 23 | 24 | if argv[2].lower() in ["true", "1"]: 25 | use_labels = True 26 | else: 27 | use_labels = False 28 | 29 | return path_to_folder, use_labels 30 | 31 | 32 | def proportional_resize(image, max_side): 33 | if image.shape[0] > max_side or image.shape[1] > max_side: 34 | if image.shape[0] > image.shape[1]: 35 | height = max_side 36 | width = int(height / image.shape[0] * image.shape[1]) 37 | else: 38 | width = max_side 39 | height = int(width / image.shape[1] * image.shape[0]) 40 | else: 41 | height = image.shape[0] 42 | width = image.shape[1] 43 | 44 | return cv2.resize(image, (width, height)) 45 | 46 | 47 | def scan(argv): 48 | path_to_folder, use_labels = parse_argv(argv) 49 | walks = list(os.walk(path_to_folder)) 50 | i = 0 51 | 52 | while i < len(walks): 53 | path, directories, files = walks[i] 54 | files = [file for file in files if not file[0] == "."] 55 | j = 0 56 | 57 | while j < len(files): 58 | file = files[j] 59 | 60 | _, extension = os.path.splitext(file) 61 | 62 | if extension == ".dcm" and dicom_support: 63 | parsed = dicomparser.DicomParser(path + os.sep + file) 64 | image = np.array(parsed.GetImage(), dtype=np.uint8) 65 | 66 | if parsed.GetImageData()["photometricinterpretation"] == "MONOCHROME1": 67 | image = 255 - image 68 | 69 | image = cv2.equalizeHist(image) 70 | image = cv2.medianBlur(image, 3) 71 | elif extension in [".bmp", ".pbm", ".pgm", ".ppm", ".sr", ".ras", ".jpeg", ".jpg", ".jpe", ".png", 72 | ".tiff", ".tif"]: 73 | image = cv2.imread(path + os.sep + file, 0) 74 | image = cv2.equalizeHist(image) 75 | image = cv2.medianBlur(image, 3) 76 | else: 77 | j += 1 78 | continue 79 | 80 | scaled_image = proportional_resize(image, 512) 81 | right_lung_hog_rectangle = lf.find_right_lung_hog(scaled_image) 82 | left_lung_hog_rectangle = lf.find_left_lung_hog(scaled_image) 83 | right_lung_lbp_rectangle = lf.find_right_lung_lbp(scaled_image) 84 | left_lung_lbp_rectangle = lf.find_left_lung_lbp(scaled_image) 85 | right_lung_haar_rectangle = lf.find_right_lung_haar(scaled_image) 86 | left_lung_haar_rectangle = lf.find_left_lung_haar(scaled_image) 87 | color_image = cv2.cvtColor(scaled_image, cv2.COLOR_GRAY2BGR) 88 | 89 | if right_lung_hog_rectangle is not None: 90 | x, y, width, height = right_lung_hog_rectangle 91 | cv2.rectangle(color_image, (x, y), (x + width, y + height), (59, 254, 211), 2) 92 | if use_labels: 93 | cv2.putText(color_image, "HOG Right", (x + 5, y + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 94 | (59, 254, 211), 1) 95 | 96 | if left_lung_hog_rectangle is not None: 97 | x, y, width, height = left_lung_hog_rectangle 98 | cv2.rectangle(color_image, (x, y), (x + width, y + height), (59, 254, 211), 2) 99 | if use_labels: 100 | cv2.putText(color_image, "HOG Left", (x + 5, y + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 101 | (59, 254, 211), 1) 102 | 103 | if right_lung_lbp_rectangle is not None: 104 | x, y, width, height = right_lung_lbp_rectangle 105 | cv2.rectangle(color_image, (x, y), (x + width, y + height), (130, 199, 0), 2) 106 | if use_labels: 107 | cv2.putText(color_image, "LBP Right", (x + 5, y + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 108 | (130, 199, 0), 1) 109 | 110 | if left_lung_lbp_rectangle is not None: 111 | x, y, width, height = left_lung_lbp_rectangle 112 | cv2.rectangle(color_image, (x, y), (x + width, y + height), (130, 199, 0), 2) 113 | if use_labels: 114 | cv2.putText(color_image, "LBP Left", (x + 5, y + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 115 | (130, 199, 0), 1) 116 | 117 | if right_lung_haar_rectangle is not None: 118 | x, y, width, height = right_lung_haar_rectangle 119 | cv2.rectangle(color_image, (x, y), (x + width, y + height), (245, 199, 75), 2) 120 | if use_labels: 121 | cv2.putText(color_image, "HAAR Right", (x + 5, y + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 122 | (245, 199, 75), 1) 123 | 124 | if left_lung_haar_rectangle is not None: 125 | x, y, width, height = left_lung_haar_rectangle 126 | cv2.rectangle(color_image, (x, y), (x + width, y + height), (245, 199, 75), 2) 127 | if use_labels: 128 | cv2.putText(color_image, "HAAR Left", (x + 5, y + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 129 | (245, 199, 75), 1) 130 | 131 | cv2.imshow("lungs-finder", color_image) 132 | found_lungs = lf.get_lungs(scaled_image) 133 | 134 | if found_lungs is not None: 135 | cv2.imshow("Found lungs", found_lungs) 136 | 137 | code = cv2.waitKey(0) 138 | 139 | while code not in [2, 3, 27, 32]: 140 | code = cv2.waitKey(0) 141 | 142 | if code == 27: 143 | exit(0) 144 | elif code in [3, 32]: 145 | j += 1 146 | else: 147 | if j > 0: 148 | j -= 1 149 | else: 150 | if i > 0: 151 | i -= 2 152 | i += 1 153 | 154 | 155 | if __name__ == "__main__": 156 | sys.exit(scan(sys.argv)) 157 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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-------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | BOOST 5 | LBP 6 | 60 7 | 30 8 | 9 | GAB 10 | 9.9900001287460327e-01 11 | 5.0000000000000000e-01 12 | 9.4999999999999996e-01 13 | 1 14 | 100 15 | 16 | 256 17 | 1 18 | 11 19 | 20 | 21 | <_> 22 | 3 23 | -1.0599268674850464e+00 24 | 25 | <_> 26 | 27 | 0 -1 30 -1 -1718102877 -784105469 -2053910325 -226238257 28 | -1073643510 -936910453 -1409291537 29 | 30 | -9.5274007320404053e-01 9.4084650278091431e-01 31 | <_> 32 | 33 | 0 -1 12 -3145729 -782778233 1367640067 -246725729 25362667 34 | -1065320438 1619073163 -645185297 35 | 36 | -9.4263368844985962e-01 9.2367261648178101e-01 37 | <_> 38 | 39 | 0 -1 5 -137494529 -140910333 -1853271843 -551583741 40 | 1074907579 159940611 8962187 1472954511 41 | 42 | -9.8574393987655640e-01 8.3544689416885376e-01 43 | 44 | <_> 45 | 3 46 | -1.0134402513504028e+00 47 | 48 | <_> 49 | 50 | 0 -1 21 -136314881 905286109 -1860595217 1066909831 51 | -1060976485 -1148583775 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--------------------------------------------------------------------------------