Python library for pathology image analysis
This project is part of my PhD thesis to analyse histopathological images. Especially, the breast cancer hematoxylin and eosin-stained images from BreCaHAD: a dataset for breast cancer histopathological annotation and diagnosis
- Optical density transform
- Color deconvolution local_binary_patternslocal_binary_patterns
$ pip install python-patho$ python demo.py>>>frompypath.transformimportconvert_RGB_to_OD>>>importcv2>>>I_BGR=cv2.imread('images/he.png')
>>>I_RGB=cv2.cvtColor(I_BGR, cv2.COLOR_BGR2RGB)
>>>I_OD=convert_RGB_to_OD(I_RGB)
>>>frompypath.stain_extractorimportHE_color_decon>>>I_H, I_E=HE_color_decon(I_RGB)
>>>frompypath.textureimportcal_lbp>>>I_LBP=cal_lbp(I_BGR)
>>>frompypath.utilsimportthreshold>>>frompypath.transformimportmopho_process>>>>>>src_path='IHC_IMAGE.jpg'>>>color_img=cv2.imread(src_path)
>>>color_img=staintools.LuminosityStandardizer.standardize(color_img)
>>>>>>gray=cv2.cvtColor(color_img, cv2.COLOR_BGR2GRAY)
>>>gray=threshold(gray, 220)
>>>cells_image=mopho_process(gray, gen_kernels())
>>>>>>contours, hierarchy=cv2.findContours(cells_image, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
>>>cv2.drawContours(color_img, contours, -1, (255,0,0), 3)
>>>frompypath.cell_processorimportselect_cell>>>color_cell, binary_cell=select_cell(color_img, contours, 161)